manual of petroleum measurement standards chapter...

This document is not an API Standard; it is under consideration within an API technical committee but has not received all approvals required to become an API Standard. It shall not be reproduced or circulated or quoted, in whole or in part, outside of API committee activities except with the approval of the Chairman of the committee having jurisdiction and API staff. Copyright API. All rights reserved.

Manual of Petroleum Measurement Standards Chapter 20.4 Phase Behavior Applications in Upstream Measurement First Edition


ii

Table of Contents

1 Scope ........................................................................................................................... 5

2 Normative References .................................................................................................. 5

3 Terms, Definitions, Abbreviations and Symbols ............................................................. 5 3.1 Terms and Definitions................................................................................................. 5 3.2 Abbreviations and Symbols ........................................................................................ 9

4 Overview of Phase Behavior in Upstream Measurement ............................................. 10 4.1 General .................................................................................................................... 10 4.2 Applicability .............................................................................................................. 11 4.3 Key Elements and Workflow ..................................................................................... 11

5 Theoretical Quantity Determination for Allocation Using PVT Fluid Properties ............. 13 5.1 Application Development .......................................................................................... 13 5.2 Application Implementation ....................................................................................... 21

6 Theoretical Quantity Determination for Allocation Using a Process Simulation Model (PSM) ......................................................................................................................... 24

6.1 Application Development .......................................................................................... 24 6.2 Application Implementation ....................................................................................... 35

7 Multiphase and Wet Gas Flow Meter (MPFM) Configuration ........................................ 38 7.1 Application development .......................................................................................... 38 7.2 Application Implementation ....................................................................................... 45

8 Fluid Sample and PVT Fluid Property Quality Assurance (QA) .................................... 47 8.1 Application development .......................................................................................... 47 8.2 Application Implementation ....................................................................................... 49

9 Flow Modeling (Virtual Flow Metering) ........................................................................ 49 9.1 Application development .......................................................................................... 49 9.2 Application Implementation ....................................................................................... 56

10 PVT Fluid Property Interpolation to Alternate Process Conditions ................................ 58 10.1 Application Development .......................................................................................... 58 10.2 Application Implementation ....................................................................................... 61

11 Performance Management .......................................................................................... 62 11.1 General .................................................................................................................... 62 11.2 Functional Specification Review ............................................................................... 62 11.3 Functional Specification Modifications ...................................................................... 62 11.4 Validation and Reproducibility of Results .................................................................. 63 11.5 Performance Monitoring and Reporting ..................................................................... 63 11.6 Out-of-tolerance Performance Management ............................................................. 63

Annex A .............................................................................................................................. 64

Annex B .............................................................................................................................. 65


iii

Annex C .............................................................................................................................. 76

Annex D .............................................................................................................................. 80 Annex E .............................................................................................................................. 81 Annex F .............................................................................................................................. 85 Annex G .............................................................................................................................. 87 Annex H .............................................................................................................................. 93

Bibliography ........................................................................................................................ 97


iv

Introduction This document establishes a framework to develop, implement, and manage the application of hydrocarbon phase behavior in upstream measurement. The applied phase behavior modeling addressed in this document refers to a process simulation model (PSM) incorporating an equation of state (EOS) description of the phase behavior, or pressure, volume, temperature (PVT) properties, of the fluids within the modeled process. The intent of this document is to provide operators with a consistent and transparent approach for applying and managing EOS-based phase behavior applications within an upstream measurement system. It is not intended to prescribe a particular mathematical phase estimation (i.e. EOS), process simulation (i.e. PSM), measurement, or allocation method.

Additionally, guidance is provided regarding the application of the suite of API Manual of Petroleum Measurement Standards (MPMS) Chapter 20 documents applicable to phase behavior applications in upstream measurement:

— API MPMS Chapter 20.1, Production Measurement and Allocation Systems;

— API MPMS Chapter 20.2, Production Allocation Measurement Using Single-Phase Devices;

— API MPMS Chapter 20.3, Measurement of Multiphase Flow;

— API MPMS Chapter 20.5, Application of Production Well Testing in Measurement and Allocation.


5

Phase Behavior Applications in Upstream Measurement

1 Scope This document provides requirements and guidelines for the application of phase behavior (i.e., pressure, volume, temperature, or PVT fluid properties) in upstream measurement. The requirements and guidelines address the development, implementation, performance management, and reproducibility of phase behavior representation used to calculate PVT fluid properties applied in the following upstream oil and gas applications:

— Theoretical quantity determination for allocation using PVT fluid properties;

— Theoretical quantity determination for allocation using a process simulation model;

— Multiphase and wet gas flow meter configuration;

— Fluid sample and PVT fluid property quality assurance;

— Flow modelling (virtual flow metering);

— PVT fluid property interpolation to alternate process conditions.

The phase behavior representation guidelines include fit-for-purpose model selection, fluid component definition, and calculation validation.

2 Normative References The following referenced documents are indispensable for the application of this document. For dated references, only the edition cited applies. For undated references, the latest edition of the referenced document applies (including any addenda/errata).

API MPMS Chapter 11.1, Temperature and Pressure Volume Correction Factors for Generalized Crude Oils, Refined Products, and Lubricating Oils

API MPMS Chapter 14.1, Collecting and Handling of Natural Gas Samples for Custody Transfer

API MPMS Chapter 20.1, Production Measurement and Allocation Systems

API MPMS Chapter 20.2, Production Allocation Measurement Using Single-phase Devices

API MPMS Chapter 20.3, Measurement of Multiphase Flow

API MPMS Chapter 20.5, Application of Production Well Testing in Measurement and Allocation

API MPMS Chapter 21.1, Flow Measurement Using Electronic Metering Systems – Electronic Gas Measurement

3 Terms, Definitions, Abbreviations and Symbols

3.1 Terms and Definitions For the purposes of this document, the following terms and definitions apply.


6

3.1.1 acentric factor An EOS parameter that provides enhanced temperature dependence of the intermolecular potential of complex fluids from simple ideal fluids.

3.1.2 actual conditions Conditions of pressure and temperature of the fluid at the point where fluid properties (i.e. PVT) or flows are measured or calculated.

3.1.3 allocation The mathematical process of determining the proportion of produced fluids from individual entities (zones, wells, fields, leases, or producing units) when compared with the total production from the entire system (reservoir, production system, and gathering systems) in order to determine value or ownership to attribute to each entity.

3.1.4 binary interaction parameter BIP An EOS fitting parameter used to account for the nonideal interaction between molecules that addresses the difference between association terms in the EOS model compared with experimental data.

3.1.5 bubble point When the pressure is lowered on a liquid held at constant temperature, the pressure at which the first bubble of vapor forms is the bubble point.

3.1.6 critical pressure Pc The pressure at the critical point, where both liquid phase and gas phase specific volumes (densities) of a fluid are equal.

3.1.7 critical temperature Tc The temperature at the critical point, where both liquid phase and gas phase specific volumes (densities) of a fluid are equal.

3.1.8 critical volume Vc The volume at the critical point, where both liquid phase and gas phase specific volumes (densities) of a fluid are equal.

3.1.9 discrete component An EOS component representing a single molecule structure, e.g. Methane, Ethane, i-Butane.


7

3.1.10 end point(s) Allocation end quantity(ies) physical location and associated thermodynamic state in the PMAS.

3.1.11 end point conditions Conditions of pressure and temperature at the end point.

3.1.12 equation of state EOS Thermodynamic equation describing the state of matter under a given set of physical conditions.

NOTE An EOS provides a mathematical relationship among the state variables pressure, temperature, and molar volume.

3.1.13 EOS tuning An adjustment of EOS parameters (e.g. Tc, Pc, binary interaction parameters) to minimize the difference between EOS-predicted PVT values and measured PVT values within the PSM domain.

3.1.14 flash gas factor FF Ratio of evolved hydrocarbon gas quantity at standard conditions (evolved from hydrocarbon liquid as it transitions from measurement point conditions to end point conditions) to the hydrocarbon liquid quantity at standard conditions.

NOTE 1 Both the evolved hydrocarbon gas and hydrocarbon liquid quantities are adjusted from end point conditions to standard conditions.

NOTE 2 For volume calculations, the flash gas factor is in units of mscf/bbl (103 m3/m3). For mass calculations, the flash gas factor is in units of lbm/lbm (kg/kg). For molar calculations, the flash gas factor is in units of mol/mol.

3.1.15 gas correction factor Bg Ratio of hydrocarbon gas quantity at measurement point conditions to the hydrocarbon gas quantity at standard conditions. NOTE For volume calculations, the gas correction factor is in units of acf/scf (m3/m3). For mass calculations, the gas correction factor is in units of lbm/lbm (kg/kg). For molar calculations, the gas correction factor is in units of mol/mol.

3.1.16 hydrocarbon dew point A temperature at a given pressure at which hydrocarbon vapor condensation begins.

3.1.17 individual theoretical quantity The quantity represented by an individual contributing meter or measurement point after conversion to a theoretical value by applying an EOS or other correction factor, usually done in order to adjust the measured quantity for comparison at the same pressure and temperature base as the master quantity.


8

3.1.18 measurement point conditions Conditions of pressure and temperature at the measurement point.

3.1.19 non-discrete component An EOS component that represents multiple molecule structures, e.g. Hexanes, Cn+, PsC.

3.1.20 oil correction factor Bo Ratio of hydrocarbon liquid quantity at measurement point conditions to the hydrocarbon liquid quantity at standard conditions. The oil correction factor is the inverse of the oil shrinkage factor, SF.

NOTE For volume calculations, the oil correction factor is in units of bbl/bbl (m3/m3). For mass calculations, the oil correction factor is in units of lbm/lbm (kg/kg). For molar calculations, the oil correction factor is in units of mol/mol.

3.1.21 oil shrinkage factor SF Ratio of hydrocarbon liquid quantity at standard conditions to the hydrocarbon liquid quantity at measurement point conditions. The oil shrinkage factor is the inverse of the oil correction factor, Bo.

NOTE For volume calculations, the oil shrinkage factor is in units of bbl/bbl (m3/m3). For mass calculations, the oil shrinkage factor is in units of lbm/lbm (kg/kg). For molar calculations, the oil shrinkage factor is in units of mol/mol.

3.1.22 pressure, volume, temperature PVT The phase behavior and description of hydrocarbon fluid physical properties for a given set of composition, pressure, and temperature.

NOTE Physical properties of interest include relative phase fraction, GOR, bubble point and hydrocarbon dew point, density, correction factors, compressibility, and viscosity.

3.1.23 process simulation model PSM A computer-based model representing physical and chemical processes (mass and energy balances) to predict process conditions (e.g. pressures, temperatures, flows, compositions) as well as thermophysical properties (e.g. density, viscosity, heat capacity).

3.1.24 pseudo-component PsC A grouping of several compositional components as a single component in an EOS phase description model.

3.1.25 solution condensate-gas ratio rs


9

Ratio of condensed hydrocarbon liquid quantity at standard conditions (condensed from hydrocarbon gas as it transitions from measurement point conditions to end point conditions) to the hydrocarbon gas quantity at standard conditions.

NOTE 1 Both the evolved hydrocarbon gas and hydrocarbon liquid quantities are adjusted from end point conditions to standard conditions.

NOTE 2 For volume calculations, the solution condensate-gas ratio is in units of bbl/mscf (m3/103 m3). For mass calculations, the solution condensate-gas ratio is in units of lbm/lbm (kg/kg). For molar calculations, the solution condensate-gas ratio is in units of mol/mol.

3.1.26 surrogate component A single discrete component used to represent a group of components with similar properties.

NOTE 1 The surrogate differs from the PsC by having the well-defined properties of a discrete component but limited in the range of molecules it covers. An example of a surrogate is Ethylbenzene used to represent C8 aromatics.

3.1.27 standard conditions Pressure and temperature conditions used to normalize quantities for allocation and/or sales (e.g. 14.696 psia, 60°F; 101.325 kPa, 15°C).

3.1.28 vapor-liquid equilibrium VLE A state where vapor and liquid coexist at the same pressure, temperature, and total volume with no net mass transfer between phases.

3.1.29 volume shift A constant correction term that refers to the translation of the repulsive hard sphere volume in a cubic EOS by the corresponding states approach, used to adjust an EOS-calculated molar volume to improve liquid density calculations.

3.1.30 water correction factor Bw Ratio of water quantity at measurement point conditions to water quantity at standard conditions.

NOTE For volume calculations, the water correction factor is in units of bbl/bbl (m3/m3). For mass calculations, the water correction factor is in units of lbm/lbm (kg/kg). For molar calculations, the water correction factor is in units of mol/mol.

3.2 Abbreviations and Symbols For the purposes of this document, the following abbreviations and symbols apply.

acf actual cubic feet

bbl barrel

Bg gas correction factor

Bo oil correction factor


10

Bw water correction factor

EOS equation of state

FF flash gas factor

FWKO free water knockout

GOR gas-oil ratio

kg kilogram

KPI key performance indicator

lbm pounds mass

m3 cubic meter

mscf thousand standard cubic feet

MW molecular weight

Pc critical pressure

PFD process flow diagram

PMAS production measurement and allocation system

PsC pseudo-component

PSM process simulation model

PVT pressure, volume, temperature

rs solution condensate-gas ratio

scf standard cubic feet

SF oil shrinkage factor

Tb normal boiling point temperature

Tc critical temperature

Vc critical volume

VLE vapor-liquid equilibrium

VRU vapor recovery unit

4 Overview of Phase Behavior in Upstream Measurement

4.1 General Reservoir fluids undergo physical changes upon movement through a production process prior to becoming stabilized hydrocarbon liquids and dry hydrocarbon gas. These physical changes are due to the inherent variation in pressure and temperature over the entire production process and are characterized by the VLE or PVT properties of the fluids, otherwise referred to as phase behavior. The phase behavior of the various produced fluids throughout a production process is a distinctive but integral


11

part of upstream measurement. In particular, phase behavior is applied to upstream measurement applications including theoretical quantity determination for allocation, configuration of multiphase and wet gas flow meters, fluid sample quality assurance, flow modeling (virtual metering), and interpolation of PVT properties among alternate process conditions.

4.2 Applicability This document applies to upstream measurement in general, and specifically is intended to address phase behavior within the suite of API MPMS Ch. 20 documents in the determination and assurance of equitable allocation of production quantities. It is not the intent of this document to specify or prescribe meter types, allocation methodologies, flow modeling techniques or specific simulation software packages. Nor is it the intent of this document to encourage the use of one approach over another.

Referenced single-phase flow metering should follow API MPMS Ch. 20.2

Referenced multiphase and wet gas flow metering should follow API MPMS Ch. 20.3.

Allocation of production quantities should follow API MPMS Ch. 20.1.

Production well testing and the application of well flow modeling (virtual metering) should follow API MPMS Ch. 20.5.

4.3 Key Elements and Workflow Applying phase behavior in upstream measurement applications shall incorporate development, implementation, and performance management activities that ensure the application is capable of meeting measurement and/or allocation requirements. Key elements that shall be performed to establish and maintain an application of phase behavior include:

— application development (specific to the intended application, refer to Sections 5.1, 6.1, 7.1, 8.1, 9.1, 10.1), incorporating:

— relevant phase behavior parameter definition (i.e. the parameters of interest to the application);

— functional specification (i.e. fluid characterization, process description, determination of input/outputs, simulation tools, and validation and acceptance criteria);

— application implementation (specific to the intended application, refer to Sections 5.2, 6.2, 7.2, 8.2, 9.2, 10.2), incorporating:

— validation of fluid characterizations, simulation tools, and input data;

— determination and validation of output results;

— performance management (refer to Section 11).

Figure 1 outlines the key elements, the associated workflow and supporting activities used to establish and maintain an application of phase behavior in upstream measurement.


12

Figure 1 – Phase Behavior Application Key Elements and Workflow


13

5 Theoretical Quantity Determination for Allocation Using PVT Fluid Properties

5.1 Application Development

5.1.1 General The operator shall be responsible for the development of a PVT fluid properties application when PVT fluid properties are used in a PMAS. The PVT application or PVT tool incorporates an EOS and is used to develop PVT factors applied in the PMAS. The factors account for volumetric and mass changes due to phase conversions and can provide a more rigorous theoretical quantity determination than laboratory generated factors. Where laboratory factors are generally products of single stage flash, blind to actual processing conditions, the PVT tool can capture the effects of multistage processing with heat input and removal. The PVT tool does not address the effects of commingling PMAS source streams (refer to Section 6).

5.1.2 Phase behavior parameter definition: required outputs

5.1.2.1 Oil shrinkage factor, SF and flash gas factor, FF The PVT tool shall include a process that emulates the hydrocarbon liquid stabilization process of the source liquid to end conditions. The PVT tool shall be valid for the range of temperatures and pressures that include allocation source conditions, conditions at points of separation, and end point conditions. The output of the process shall be a SF and an FF, (refer to API MPMS Ch. 20.1), from source to end point conditions.

5.1.2.2 Gas correction factor, Bg and solution condensate-gas ratio, rs The PVT tool shall include a process that emulates the hydrocarbon gas process of the source gas to end conditions. The PVT tool shall be valid for the range of temperatures and pressures that include allocation source conditions, conditions at points of separation, conditions at compression and cooling, and endpoint conditions. The output of the process shall be a Bg and a rs, (refer to API MPMS Ch. 20.1), from source to endpoint conditions.

5.1.2.3 Other parameters The PVT tool may include other processes and outputs. In this case, the PVT tool shall be valid for the range of temperature and pressure conditions to which it is applied. The output of the process shall be a in accordance with API MPMS Ch. 20.1, if applicable.

5.1.3 Fluid Characterization

5.1.3.1 General A fluid characterization process should be included in the PVT tool however, the fluid characterization may be performed as a separate process or omitted from the process if laboratory analytical data is demonstrated to yield adequate results.

5.1.3.2 Measurement The following is a list of field data that may be used in source fluid characterization:

— liquid bubble point pressure (separation pressure);

— gas dew point temperature (separation temperature);

— liquid flowing density (separation densitometer);


14

— gas oil ratio (oil meter and gas meter);

The characterization process may include some or all these data. Other field data may also be used. Data source equipment shall be identified and documented.

The following is a list of laboratory analysis data for use in source fluid characterization:

— liquid composition;

— gas composition;

— non-discrete component MW and liquid density;

— fluid MW and liquid density;

— liquid shrinkage factor;

— liquid flash gas factor;

— liquid flash gas composition;

— residual oil composition.

The characterization process may include some or all these data. Other laboratory data may also be used.

5.1.3.3 Component Set 5.1.3.3.1 General This Standard does not prescribe a specific component set for the PVT tool. The selection of a component set should be based on factors including range and types of fluids, variation in composition, and available sampling and laboratory services. The component set may include surrogate components and PsC (refer to Annex B). The following properties and parameters should be defined for each component in the set:

— molecular weight (MW),

— Pc (critical pressure),

— Tc (critical temperature),

— Vc (critical volume),

— Tb (normal boiling temperature),

— standard density,

— acentric factor,

— binary interaction parameters, and

— volume translation when applicable.


15

The component set shall be structured to adequately represent all process streams within the PMAS and shall align with a laboratory analysis (refer to 5.1.4.7). The EOS shall use a single component set for the allocation source streams.

User developed properties may be assigned to components. Some useful component properties are not included in the applied software library or the values in the library are not consistent with the values agreed to or required by permit.

EXAMPLE Gross Heating Values (GHV) found in GPA-2145 can be assigned to individual components such that the GHV of endpoint streams can be calculated directly by the PVT tool and in accordance with GPA-2172.

NOTE In general, an extensive well-defined component list can minimize the amount of tuning required. Abbreviated lists tend to require more tuning and are applicable over a more limited range of source operating conditions.

The component set should not include water unless it can be demonstrated that the inclusion of water has a material improvement on the allocation results.

5.1.3.3.2 Discrete Components The PVT tool shall include the following discrete components:

— Nitrogen

— Carbon Dioxide

— Methane

— Ethane

— Propane

— iso-Butane

— n-Butane

— iso-Pentane

— n-Pentane

Other discrete components may be included when there are corresponding source fluid sample analyses containing the discrete component. Discrete components may be removed from the set if no source fluid sample analyses contain the component.

Discrete components may be included to act as surrogate components for defined component groups (refer to Annex B).

Discrete components shall not be used to represent carbon number groups.

EXAMPLE N-Hexane should not be used to represent hexanes, n-Heptane to represent heptanes, or n-Octane to represent octanes.

5.1.3.3.3 Pseudo-Components (PsC) PsC shall be developed from laboratory supplied data including molecular weight and liquid density of the non-discrete components. Additional information such as boiling temperature may be used.


16

PsC properties and parameters not provided by the laboratory may be developed by applying correlations to the laboratory supplied data or by allowing the applied simulation software to determine them.

PsC properties, parameters, and fractions may be developed by lumping or de-lumping laboratory supplied component properties and fractions.

The fewest number of PsC should be used while meeting the PVT tool acceptance criteria. Both PsC that are applicable across multiple allocation sources and PsC that are source specific may be used.

5.1.3.4 EOS This Standard does not prescribe a specific EOS for use in a PVT tool. The EOS applied shall be valid for the range of fluids and process conditions applicable to the PMAS.

When fluid characterization is applied, an EOS tuning process should incorporate the following:

— Methodology;

— target parameters;

— fitting parameters;

— tuning parameters;

— validation methods and criteria.

Table 1 below includes a list of typical target, fitting, and tuning parameters.

Table 1: Target, fitting, and tuning parameters

Target Parameters Fitting Parameters Tuning Parameters

liquid sample bubble point

gas sample dew point

shrinkage factor

flash factor

separator GOR

gas sample composition relative to equilibrium gas of liquid sample

flash gas composition

binary interaction parameters (BIP)

volume shift

PsC MW

PsC Density

PsC boiling temperature

PsC critical properties

PsC acentricity

NOTE Target parameters are typically measured or observed fluid properties and factors that are essential parameters to the EOS results. Fitting parameters are not considered fluid properties and exist for the purpose of fitting the EOS to observed properties. Tuning parameters are nonessential fluid properties that are adjusted such that the EOS matches the observed for essential properties.

The number and type of target parameters used shall be established as part of a tuning methodology development process. Limitations on fitting and tuning parameters shall be established as part of this process.


17

The EOS shall be tunable with each new composition. The tuning process may be automated to facilitate the timeliness, repeatability, and auditability of the process.

When the PsC is fully defined prior to tuning, the tuning method should include tuning the EOS using fitting parameters. The tuning parameters should be used only when a fit is not achieved with fitting parameters. The fitting parameters can be used to concentrate on specific target parameters while tuning parameters tend to impact multiple target parameters. The initial fitting parameters listed in Table 2 should be used.

Table 2: Fitting parameter for target parameter

Target Parameter Fitting Parameter

bubble point BIP, starting with methane - largest PsC

dew point BIP, starting with methane - largest PsC

shrinkage factor volume translation, starting with PsC

flash factor BIP, starting with largest discrete component - largest PsC

separator GOR volume translation, starting with PsC

gas sample composition BIP for largest PsC

flash gas composition BIP for largest PsC

EOS tuning methods, target parameters, fitting parameters, and tuning parameters shall be documented in the functional specification. Citations to published papers which document the EOS tuning may be included. Tuning methods shall be reproducible and auditable

5.1.3.5 Correlations Correlations may be used in place of the EOS to determine tuning and fitting parameter values for use in the PVT tool. The correlation used shall not be proprietary and shall be documented in the functional specification.

5.1.4 Functional Specification

5.1.4.1 General A functional specification shall be developed and agreed to by the affected parties prior to placing the PSM in service. The functional specification shall include key assumptions, descriptions, and design considerations for the determination of the configuration parameter values. The functional specification shall also include validation methods and acceptance criteria, and supporting information on EOS tuning, if applicable.

5.1.4.2 Process Description The production process description shall be developed and maintained as a process flow diagram (PFD) prior to implementation and documented as part of the functional specification.

The PFD shall include all:

— allocation sources;

— other contributing hydrocarbon inlet streams;


18

— points of liquid and gas separation;

— stages of pumping and compression;

— points of heat addition and removal;

— fluid flow paths;

— recycle streams of condensed liquids from compression;

— sampling points;

— allocation endpoints.

Annex A contains an example of an allocation PFD. It shows the process path, points of phase separation, measurement, pumping, compression, and recirculation.

5.1.4.3 Simulation Tools The functional specification shall document the type and precise version of the simulation software used including EOS, outside correlations and methods and all applied settings. Proprietary software not commercially available shall not be used.

The PVT tool may contain a fluid characterization process. The PVT tool can be split into a liquid composition tool and a gas composition tool. Figue1 below contains an example liquid PVT tool while Figure 2 contains an example gas PVT tool.

Figure 2: Process environment view of an example liquid PVT tool

NOTE1 For this tool, liquid composition and conditions along with the pressure and temperature of three stages of separation. The output is a SF and FF for the liquid composition. This SF and FF will typically not match lab generated SF and FF because the laboratory factors would not account for the heat input and the multiple stages of separation. NOTE2 Figure 2 and Figure 3 show the example tools as viewed in the process simulation environment. Another aspect to the tools is the fluid property environment. It is in this environment that the PVT fluid properties are defined.


19

Figure 3: Process environment view of an example gas PVT tool

NOTE3 For gas PVT tool, gas composition and conditions along with the pressure and temperature of three points of separation are the input. The output is a Bg and rs for the gas composition. This Bg and rs will typically not match lab generated Bg and rs because the laboratory factors would not account for the separation, compression, and cooling.

The PVT tool shall be updated along with the functional specification PFD when process changes are made that can impact the PVT factor results.

5.1.4.4 Input Data Requirements 5.1.4.4.1 Fluid characterization input requirements When a source fluid characterization or tuning process is used, the initial input into the PVT tool may include:

— The source gas stream composition,

— The source liquid stream composition,

— non-discrete component MW and Liq. Density,

— Separation pressure at the time of the sampling,

— Separation temperature at the time of the sampling, and

— Laboratory determined parameters to use as target parameters.

5.1.4.4.2 PVT tool input requirements When the allocation process is run independently of the fluid characterization process, the allocation input into the PVT tool may include:

— Source pressures and temperatures,

— Endpoint pressures and temperatures,

— Pressure and temperature at separation points, and


20

— Pressure and temperature at points of enthalpy change.

5.1.4.4.3 PVT tool (without characterization) input requirements When there is no fluid characterization process, the allocation input into the PVT tool may include:

— The source gas stream composition,

— The source liquid stream composition,

— non-discrete component MW and Liq. Density,

— Source pressures and temperatures,

— Endpoint pressures and temperatures,

— Pressure and temperature at separation points, and


5.1.4.4.4 Sampling and laboratory analysis requirements The compositional input shall be traceable to a laboratory analysis. All laboratory obtained input data shall be obtained in accordance with a prescribed applicable industry standard. Proprietary lab analyses shall not be used. Where no standard is indicated, a full description of the method used to determine the composition, property, or factor shall be documented and included in the functional specification.

Composite compositional analyses shall not be used for an allocation PVT tool unless it can be demonstrated that the composite sampling period matches the allocation period. The periods are considered matching if they start on the same day and end on the same day. If an allocation source has a material change in composition, a sample representing the new composition shall be taken and processed for inclusion in the allocation. If an allocation source conditions change, the existing valid composition may be conditioned in accordance with Section 10 or a new sample may be taken and processed for inclusion in the allocation. Factors that define a material change shall be established and documented.

The source liquid and gas compositions shall be determined from samples taken at the same time. The separation pressure and temperature shall be recorded from separator instrumentation when possible. Sampling pressure and temperature shall not be used if different than separation pressure.

The PSM shall include a conditioning function in accordance with Section10 to ensure that source fluid compositions are representative of the current allocation period.

5.1.4.4.5 Field data requirements A list of inputs along with the units of measurement and associated devices shall be included in the functional specification. Table 3 below is an example input listing.

Table 3: Example input list

Input Units of Measurement Associated Device

Separator A Pressure psig PIT-123

Separator A Temperature °F TIT-123


21

The minimum requirements for input data, including the methods and processes utilized to obtain the input data and the manipulation of data such as flow weighting, shall be and documented and included in the functional specification.

5.1.4.5 PSM Outputs The output parameters shall match the PMAS requirements (refer to API MPMS Ch. 20.1).

The unit of measure and number of significant figures for each output parameter shall be included.

The uncertainty for calculated output parameters should be provided. Uncertainty determination methodology and requirements for the output parameters should be documented.

5.1.4.6 Validation and Acceptance Criteria The PVT tool validation methods, validation frequency, and acceptance criteria shall be established prior to implementation and documented in the functional specification.

All processes used to aid PVT tool validation, including methodologies for EOS tuning, shall be established prior to implementation and documented in the functional specification.

The input composition validation methods and acceptance criteria shall be in accordance with Section 47 and established prior to implementation and documented in the functional specification.

5.2 Application Implementation

5.2.1 General The operator shall be responsible for the implementation of a PVT tool when a PVT tool is used to describe phase behavior for a PMAS. Maintaining data quality are key to the PVT tool performance while a systematic application of the PVT tool facilitates repeatability and auditability. Implementation of the PVT tool shall be in accordance with the implementation of the PMAS (refer to API MPMS Chap. 20.1).

5.2.2 Fluid characterization validation Fluid quality validation shall be conducted in accordance with the fluid quality confirmation documentation (refer to Section 5.1.4.5).

A log of rejected sample pairs along with the basis for rejection shall be maintained. A review and reconciliation of the rejections listed in this log shall be conducted on a periodic basis. The frequency, criteria, and remediation plans, if any, shall be included in the fluid quality confirmation documentation.

Often in fluid characterization, the tuning process will mask compositional and methodology issues as the target parameters are driven to match observed conditions and properties. The acceptance criteria associated with fluid characterization should be based on multiple factors to ensure that quality issues are addressed. Factors that may be used include:

— Basic compositional logic (a single component fraction out of bounds);

— Thermodynamic relationship between liquid and gas compositions of the sample pair (equilibrium);

— Tuning objective met (EOS match observed);

— Degree to which fitting and tuning parameters are adjusted (limitations).


22

5.2.3 Simulation tool validation

5.2.3.1 Overall Material and Energy Balance Validation An overall material and energy balance (refer to Annex H) shall be performed for each allocation period where a PVT tool is used. Errors between individual theoretical quantities, energy content, and sales data indicate problems related to measurement, fluid characterization, or EOS. A material and energy balance is a tool that can facilitate troubleshooting and problem resolution.

5.2.4 Input data validation

5.2.4.1 Composition input data validation Laboratory oversight and auditing shall be conducted on a periodic basis and as part of the operation of the PMAS. (refer to API MPMS Chap. 20.1)

The reported compositional analyses’ conditions shall match the source conditions at the time the sample was taken. For samples taken at a liquid/gas separation point, the source conditions shall mean the pressure and temperature of the separator.

MW and liquid density of the discrete components contained in the laboratory analysis shall align with the EOS MW and liquid density of the same components. Differences found between values should be evaluated for impact to the allocation results and reconciled, as necessary.

5.2.4.2 Process input data validation Instrument calibration shall be monitored as part of the operation of the PMAS. (refer to API MPMS Chap. 20.1)

Input process data for PVT tool implementation include temperatures, pressures, and flow volume measurements as documented in the functional specification of the PVT tool. The specified input process data shall be reviewed for accuracy prior to each run of the PVT tool.

NOTE Temperature, pressure, and flow measurements might exhibit high uncertainties that can adversely affect the input process data for the PVT tool.

In reviewing the input process data:

— the operator shall verify that the input flow measurement equipment is installed, operated, and maintained per API MPMS Chapter 20.2 for single-phase measurement devices and API MPMS Chapter 20.3 for multiphase measurement devices.

— the operator should verify that the temperature and pressure transmitters are installed per API Recommended Practice 551;

— the operator should verify and calibrate temperature and pressure transmitters per API MPMS Chapter 21.1.

— The operator shall input only data that have been screened. As a minimum, screened process data shall have:

— temperature and pressure data recorded during upset or shut-in periods removed,

— pressure and temperature data evaluated for continuity.

— The operator shall document any change or omission of data from the PVT tool.


23

5.2.5 Output result determination PVT tool output determination should be a documented stepwise process, following the progression outlined in Figure 4.

— The compositional and process data for the allocation period shall be validated as described in 5.2.4.

— Validated compositional data should be characterized in accordance 6.2.5.1 and conditioned in accordance in accordance with Section 10.

— Fluid characterization should be validated in accordance with 5.2.2.

— If the characterization validation fails, the sample shall be rejected.

— A second material balance should be performed in accordance with 5.2.3.

— When the material balance passes, the PVT tool may be executed.

— If the material balance fails, the source of the imbalance shall be identified and corrected.

— The output of the PVT tool is passed to the PMAS.

Figure 4: PVT development process


24

5.2.6 Output result validation The output of the PVT tool is the source theoretical quantities used by the PMAS to allocate end point quantities. The output of the PVT tool shall be validated with a material and energy balance with an emphasis on the mass balance of the phases (refer to Annex H).

PSM performance monitoring and reporting shall be incorporated into the PMAS performance monitoring and reporting program. (refer to API MPMS Chap. 20.1)

6 Theoretical Quantity Determination for Allocation Using a Process Simulation Model (PSM)


6.1.1 General The operator shall be responsible for the development of a PSM when a PSM is used to describe phase behavior for a PMAS. An allocation PSM is a model, incorporating an EOS, used to apply phase behavior in the determination of theoretical quantities for allocation (refer to API MPMS Ch. 20.1). A PSM is incorporated into a PMAS when there is a need to mitigate bias beyond what is achievable when addressing phase behavior as described in Chap 20.1 alone. This need is often driven by a disparity in fluids or difference in ownership.


6.1.2.1 PSM functionality The PSM should function both as a source fluid characterization model and as an allocation model. See Figure 5. This dual functionality is driven by the need to define fluid properties for multiple independent and diverse sources (characterization) while combining these source streams into a single model simulating the production process. The result being theoretical source quantities at the allocation end points (allocation).

Figure 5: Dual function PSM

The characterization function emulates the field conditions and laboratory analyses of the individual source streams while the allocation function emulates the hydrocarbon stabilization process of the combined streams. Because the fluid characterization is not performed using the combined streams, the


25

PSM may be divided into separate models to achieve this functionality. If the characterization function is deemed unnecessary, it need not be included.

6.1.2.2 Characterization function The PSM should include a process where source fluid data is fully characterized using known conditions, component properties, and laboratory determined factors. The results of the process serve as an EOS tuning process and an intermediate output of the PSM. This intermediate output includes a representation of a full separator stream composition for each source and the properties and parameters of source specific PsC.

Because this process is performed without the use of allocation conditions, it may be structured to perform independently of an allocation period. Since the source stream characterization is performed independently of the other source streams, it may be structured to perform on a source by source basis.

The characterization function may be omitted when a source fluid sampling and analysis regime is developed that can achieve allocation results that meet the acceptance criteria. When using this approach, the applied methodology and validation method and criteria shall be documented as part of the functional specification.

6.1.2.3 Allocation function The PSM shall include a process that emulates the hydrocarbon stabilization process of the combined source streams. The PSM shall be valid for the range of temperature and pressure conditions that include allocation source conditions, end point conditions, and intermediate conditions such as compressor discharge. The PSM shall be capable of constant updating of volumes, temperatures, and pressures as part of the periodic allocation process.

The PSM output shall include source theoretical quantities of gas and oil at standard conditions (refer to API MPMS Ch. 20.1). Other outputs may include end point compositions, component quantities, retrograde condensate volume and composition, intermediate stream compositions, and energy consumed in compression or pumping.

6.1.3 Fluid Characterization

6.1.3.1 Measurement The following is a list of field data that may be used in source fluid characterization:

— liquid bubble point pressure (separation pressure);

— gas dew point temperature (separation temperature);

— liquid flowing density (separation densitometer);

— gas oil ratio (oil meter and gas meter).

The characterization process may include some or all these data. Other field data may also be used. Data source equipment shall be identified and documented.

The following is a list of laboratory analysis data for use in source fluid characterization:

— liquid composition;

— gas composition;

— non-discrete component MW and liquid density;


26

— fluid MW and liquid density;

— liquid shrinkage factor;

— liquid flash gas factor;

— liquid flash gas composition;

— residual oil composition.

The characterization process may include some or all these data. Other laboratory data may also be used.

6.1.3.2 Component Set 6.1.3.2.1 General This Standard does not prescribe a specific component set for the PSM. The selection of a component set should be based on factors including range and types of fluids, variation in composition, and available sampling and laboratory services. The component set may include surrogate components and PsC (refer to Annex B). The following properties and parameters should be defined for each component in the set:

— molecular weight (MW),

— Pc (critical pressure),

— Tc (critical temperature),

— Vc (critical volume),

— Tb (normal boiling temperature),

— standard density,

— acentric factor,

— binary interaction parameters, and

— volume translation when applicable.

The component set shall be structured to adequately represent all process streams within the PMAS and shall align with a laboratory analysis (refer to 6.1.4.8). The EOS shall use a single component set for the allocation source streams.

User developed properties may be assigned to components. Some useful component properties are not included in the applied software library or the values in the library are not consistent with the values agreed to or required by permit.

EXAMPLE Gross Heating Values (GHV) found in GPA-2145 can be assigned to individual components such that the GHV of end point streams can be calculated directly by the PSM and in accordance with GPA-2172.

NOTE In general, an extensive well-defined component list can minimize the amount of tuning required. Abbreviated lists tend to require more tuning and are applicable over a more limited range of source operating conditions.


27

The component set should not include water unless it can be demonstrated that the inclusion of water has a material improvement on the allocation results.

6.1.3.2.2 Discrete Components The PSM shall include the following discrete components:

— Nitrogen

— Carbon Dioxide

— Methane

— Ethane

— Propane

— iso-Butane

— n-Butane

— iso-Pentane

— n-Pentane

Other discrete components may be included when there are corresponding source fluid sample analyses containing the discrete component. Discrete components may be removed from the set if no source fluid sample analyses contain the component.

Discrete components may be included to act as surrogate components for defined component groups (refer to Annex B).

Discrete components shall not be used to represent carbon number groups.

EXAMPLE N-Hexane should not be used to represent hexanes, n-Heptane to represent heptanes, or n-Octane to represent octanes.

6.1.3.2.3 Pseudo-Components (PsC) PsC shall be developed from laboratory supplied data including molecular weight and liquid density of the non-discrete components. Additional information such as boiling temperature may be used.

PsC properties and parameters not provided by the laboratory may be developed by applying correlations to the laboratory supplied data or by allowing the applied simulation software to determine them.

PsC properties, parameters, and fractions may be developed by lumping or de-lumping laboratory supplied component properties and fractions.

The fewest number of PsC should be used while meeting the PSM acceptance criteria. Both PsC that are applicable across multiple allocation sources and PsC that are source specific may be used.

6.1.3.3 EOS This Standard does not prescribe a specific EOS for use in the PSM. The EOS shall be valid for the range of fluids and process conditions applicable to the PMAS.

When fluid characterization is applied, an EOS tuning process should incorporate the following:

— Methodology;


28

— target parameters;

— fitting parameters;

— tuning parameters;

— validation methods and criteria.

Table 4 below includes a list of typical target, fitting, and tuning parameters.

Table 4: Target, fitting, and tuning parameters

Target Parameters Fitting Parameters Tuning Parameters

liquid sample bubble point

gas sample dew point

shrinkage factor

flash factor

separator GOR

gas sample composition relative to equilibrium gas of liquid sample

flash gas composition

binary interaction parameters (BIP)

volume shift

PsC MW

PsC Density

PsC boiling temperature

PsC critical properties

PsC acentricity

NOTE Target parameters are typically measured or observed fluid properties and factors that are essential parameters to the EOS results. Fitting parameters are not considered fluid properties and exist for the purpose of fitting the EOS to observed properties. Tuning parameters are nonessential fluid properties that are adjusted such that the EOS matches the observed for essential properties.

The number and type of target parameters used shall be established as part of a tuning methodology development process. Limitations on fitting and tuning parameters shall be established as part of this process.

The EOS shall be tunable with each new composition. The tuning process may be automated to facilitate the timeliness, repeatability, and auditability of the process.

When the PsC is fully defined prior to tuning, the tuning method should include tuning the EOS using fitting parameters. The tuning parameters should be used only when a fit is not achieved with fitting parameters. The fitting parameters can be used to concentrate on specific target parameters while tuning parameters tend to impact multiple target parameters. The initial fitting parameters listed in Table 5 should be used.


29

Table 5: Fitting parameter for target parameter

Target Parameter Fitting Parameter

bubble point BIP, starting with methane - largest PsC

dew point BIP, starting with methane - largest PsC

shrinkage factor volume translation, starting with PsC

flash factor BIP, starting with largest discrete component - largest PsC

separator GOR volume translation, starting with PsC

gas sample composition BIP for largest PsC

flash gas composition BIP for largest PsC

EOS tuning methods, target parameters, fitting parameters, and tuning parameters shall be documented in the functional specification. Citations to published papers which document the EOS tuning may be included. Tuning methods shall be reproducible and auditable.

6.1.3.4 Correlations Correlations may be used in place of the EOS to determine tuning and fitting parameter values for use in the PSM. The correlations used shall not be proprietary and shall be documented in the functional specification.


6.1.4.1 General A functional specification shall be developed and agreed to by the affected parties prior to placing the PSM in service. The functional specification shall include key assumptions, descriptions, and design considerations for the determination of the configuration parameter values. The functional specification shall also include validation methods and acceptance criteria, and supporting information on EOS tuning, if applicable.

6.1.4.2 Process Description The production process description shall be developed and maintained as a process flow diagram (PFD) prior to implementation and documented as part of the functional specification.

The PFD shall include all:

— allocation sources;

— other contributing hydrocarbon inlet streams;

— points of liquid and gas separation;

— stages of pumping and compression;

— points of heat addition and removal;

— fluid flow paths;

— recycle streams of condensed liquids from compression;


30

— sampling points;

— allocation endpoints.

Annex A contains an example of an allocation PFD. It shows the process path, points of phase separation, measurement, pumping, compression, and recirculation.

6.1.4.3 Simulation Tools The type and precise version of the simulation software used, including EOS, correlations and methods and all applied settings shall be documented in the functional specification. Proprietary software not commercially available shall not be used.

The PSM may be split into a fluid characterization tool and an allocation tool.

The fluid characterization tool simulates the first stage or inlet separation in the field and the laboratory shrink determination. Source analyses may be processed one at a time or in groups. The output of this tool is, in part, the input into the allocation tool. Figure 5 below contains an example fluid characterization tool.

Figure 6: Process environment view of an example fluid characterization tool NOTE1 For this tool, oil composition, GOR, and temperature are initial inputs while separator pressure, gas composition, and shrinkage factor are the target parameters. The fitting parameters are PsC BIP and volume shift. The BIP are adjusted to match the oil composition stream’s bubble point pressure to the separator pressure and the equilibrium gas composition to the gas composition stream’s composition. The volume shift is adjusted to match the ratio of the shrink stream volume / oil composition volume to the lab shrinkage factor. The Full Stream composition is made up of the oil composition stream and gas equilibrium stream compositions combined at GOR proportions.

NOTE2 Figure 6 shows the example tool as viewed in the process simulation environment. Another aspect to the tool is the fluid property environment. It is in this environment that the PsC fitting parameters are adjusted to reach target parameters.

The allocation tool simulates the production process of the combined source streams. The process layout of the tool should represent the PFD (refer to 6.1.4.2). The allocation PSM tool shall be updated along with the PFD when process changes are made that can impact the allocation results. Process equipment groups may be modeled as a single piece of equipment when operating in parallel or when operating in series with no intermediate side streams.


31

The allocation PSM tool can represent the entire PSM when fluid characterization is not performed. The characterization tool and allocation tool may be combined into a single simulation model.

6.1.4.4 Input Data Requirements 6.1.4.4.1 Fluid characterization input requirements When a source fluid characterization or tuning process is used, the initial input into the PSM may include:

— The source gas stream composition;

— The source liquid stream composition;

— The ratio of gas volume to liquid volume at the time of the samples;

— non-discrete component MW and Liq. Density;

— Separation pressure at the time of the sampling;

— Separation temperature at the time of the sampling;

— Laboratory determined parameters to use as target parameters:

— Shrinkage factor;

— Flash factor.

6.1.4.4.2 Allocation process input requirements When the allocation process is run independently of the fluid characterization process, the allocation input into the PSM may include:

— Source gas quantities;

— Source liquid quantities;

— Fuel and flare quantities;

— Circulated quantities;

— Intermediate measured quantities;

— Source pressures and temperatures;

— Endpoint pressures and temperatures;

— Pressure and temperature at separation points;


6.1.4.4.3 Allocation process only input requirements When there is no fluid characterization process, the allocation input into the PSM may include:

— The source gas stream composition;

— The source liquid stream composition;


32

— non-discrete component MW and Liq. Density;

— Source gas quantities;

— Source liquid quantities;

— Fuel and flare quantities;

— Circulated quantities;

— Intermediate measured quantities;

— Source pressures and temperatures;

— Endpoint pressures and temperatures;

— Pressure and temperature at separation points;


6.1.4.4.4 Sampling and laboratory analysis requirements The compositional input shall be traceable to a laboratory analysis. All laboratory input data shall be obtained in accordance with a prescribed applicable industry standard. Proprietary lab analyses shall not be used. Where no standard is indicated, a full description of the method used to determine the composition, property, or factor shall be documented and included in the functional specification.

Composite compositional analyses shall not be used for an allocation PSM unless it can be demonstrated that the composite sampling period matches the allocation period. The periods are considered matching if they start on the same day and end on the same day.

The source liquid and gas compositions shall be determined from samples taken at the same time. The separation pressure and temperature shall be recorded from separator instrumentation when possible. Sampling pressure and temperature shall not be used if different than separation pressure.

The PSM shall include a conditioning function (refer to Section 10) to ensure that source fluid compositions are representative of the current allocation period source fluids.

6.1.4.4.5 Field data requirements A list of inputs along with the units of measurement and associated device shall be included in the functional specification. Table 6 below is an example input listing.

Table 6: PSM field data input list

Input Units of Measurement Associated Device

Separator A Pressure psig PIT-123

Separator A Temperature °F TIT-123

Separator A Oil Volume actual barrels FIT-123L

Separator A Gas volume mscf FIT-123G

The minimum requirements for the input data, including the methods and processes utilized to obtain the input data and the manipulation of data such as flow weighting, shall be documented and included in the functional specification.


33

6.1.4.5 PSM Output result requirements 6.1.4.5.1 Intermediate outputs (fluid characterization) When characterization and allocation are separate functions in the PSM, the fluid characterization parameters should be saved as an intermediate output from the PSM. This output should include all component specific properties and parameters in a form that can be readily incorporated into the allocation function of the PSM. Table 7 contains an example intermediate output listing.

In addition to the component properties and parameters, a full stream composition for each source stream may also be generated. This output can be conditioned to the current allocation period conditions and can be used for multiple allocations when only the operating conditions change from period to period but not the compositional makeup of the source stream. Table 8 contains an example compositional output listing.

Table 7: Intermediate PSM output consisting of component properties and parameters for use in the PSM

Source A PsC Source B PsC Source C PsC

Binary Interaction Parameters component-PsC

N2 X X X

CO2 X X X

C1 X X X

C2 X X X

C3 X X X

iC4 X X X

NC4 X X X

iC5 X X X

NC5 X X X

surrogate1 X X X

surrogate2 X X X

surrogate3 X X X

Properties & Parameters

PsC MW X X X

PsC Liq. Density X X X

PsC Vol. Shift X X X

NOTE Properties and parameters for the discrete and surrogate components are contained within the allocation model and do not change from allocation to allocation. PsC properties and parameters not included in Table 7 are calculated in the allocation model from the PsC MW and Density.


34

Table 8: PSM fluid characterization compositional output

Source A Source B Source C

Mole Fractions

N2 X X X

CO2 X X X

C1 X X X

C2 X X X

C3 X X X

iC4 X X X

NC4 X X X

iC5 X X X

NC5 X X X

surrogate1 X X X

surrogate2 X X X

surrogate3 X X X

source A PsC X - -

source B PsC - X -

source C PsC - - X

The PSM output shall include source theoretical quantities of gas and oil at standard conditions (refer to API MPMS Ch. 20.1). Other outputs may include end point compositions, component quantities, retrograde condensate volume and composition, intermediate stream compositions, and energy consumed in compression or pumping.

A list of outputs along with the units of measurement and associated device shall be included in the functional specification. Table 9 below is an example output listing that may be used.

Table 9: Example PSM output list

Output Units of Measurement Value

Separator A theoretical oil volume standard barrels

Separator A theoretical gas volume mscf

Separator A theoretical gas energy mmBtu

Separator A theoretical energy consumption mmBtu

6.1.4.6 Validation and Acceptance Criteria The PSM validation methods, validation frequency, and acceptance criteria shall be established prior to implementation, and documented in the functional specification.

All processes used to aid PSM validation, including methodologies for EOS tuning, shall be established prior to implementation, and documented in the functional specification.

Fluid quality confirmation documentation that describes all PMAS fluid quality related information and activities shall be provided. This documentation should clearly identify the frequency of activities, all


35

specifically cited reference standards, along with fluid quality validation parameters and associated acceptance criteria (refer to API MPMS Chap. 20.1).


6.2.1 General The operator shall be responsible for the implementation of a PSM when a PSM is used to describe phase behavior for a PMAS. Maintaining data quality are key to the PSM performance while a systematic application of the PSM facilitates repeatability and auditability. Implementation of the PSM shall be in accordance with the implementation of the PMAS (refer to API MPMS Chap. 20.1).

6.2.2 Fluid characterization validation Fluid quality validation shall be conducted in accordance with the fluid quality confirmation documentation (refer to Section 6.1.4.6).

A log of rejected sample pairs along with the basis for rejection shall be maintained. A review and reconciliation of the rejections listed in this log shall be conducted on a periodic basis. The frequency, criteria, and remediation plans, if any, shall be included in the fluid quality confirmation documentation.

Often in fluid characterization, the tuning process will mask compositional and methodology issues as the target parameters are driven to match observed conditions and properties. The acceptance criteria associated with fluid characterization should be based on multiple factors to ensure that quality issues are addressed. Factors that may be used include:

— basic compositional logic (a single component fraction out of bounds);

— thermodynamic relationship between liquid and gas compositions of the sample pair (equilibrium);

— tuning objective met (EOS match observed);

— degree to which fitting and tuning parameters are adjusted (limitations).

6.2.3 Simulation tool validation

6.2.3.1 Overall Material and Energy Balance Validation An overall material and energy balance (refer to Annex H) shall be performed for each allocation period where a PSM is used. Errors between individual theoretical quantities, energy content, and sales data indicate problems related to measurement, fluid characterization, or EOS. A material and energy balance is a tool that can facilitate troubleshooting and problem resolution.

6.2.3.2 Internal Balances Validation The comparison of theoretical PSM data to actual data collected in the production process may be used to validate the tool. These data are typically measured flash gas or intermediate compositional data used to determine if the PSM is accurate from start to finish (refer to Annex H). Often overall material and energy balances can be acceptable while internal balances are not. This can occur when the PSM is not correctly predicting the phase behavior of a fluid or combination of fluids.




36



6.2.4.2 Process input data validation Instrument calibration shall be monitored as part of the operation of the PMAS (refer to API MPMS Chap. 20.1).

Input process data for PSM implementation include temperatures, pressures, and flow volume measurements as documented in the functional specification of the PSM. The specified input process data shall be reviewed for accuracy prior to each allocation run of the PSM.

NOTE Temperature, pressure, and flow measurements might exhibit high uncertainties that can adversely affect the input process data for the PSM.


— the operator shall verify that the input flow measurement equipment is installed, operated, and maintained per API MPMS Chapter 20.2 for single-phase measurement devices and API MPMS Chapter 20.3 for multiphase measurement devices.

— the operator should verify that the temperature and pressure transmitters are installed per API Recommended Practice 551;

— the operator should verify and calibrate temperature and pressure transmitters per API MPMS Chapter 21.1.


— temperature and pressure data recorded during upset or shut-in periods removed,

— recirculated flows reconciled,

— pressure and temperature data evaluated for continuity.

— The operator shall document any change or omission of data from the PSM.

6.2.5 Output result determination

6.2.5.1 Determination of intermediate outputs (fluid characterization) Because fluid characterization is performed without the use of allocation conditions, it may be performed independently of an allocation period and the allocation process. Because the source stream characterization is performed independently of the other source streams, this process may be performed on a source by source basis.

The fluid characterization process should serve three purposes:

— compositional validation,

— fluid characterization,

— Preparation of the fluid for conditioning to allocation conditions.


37

Figure 7 below illustrates the step by step process to serve these three purposes.

Figure 7: Fluid characterization process

6.2.5.2 PSM output determination PSM output determination should be a documented stepwise process, following this progression (refer to Figure 8).

Once the source fluids are characterized, conditioned, and validated, the process data for the allocation period shall be validated as described in 6.2.6.

Once both compositional and process input data has been validated, an overall material balance shall be performed in accordance with 6.2.3.1.

If the material balance fails, the source of the imbalance shall be identified and corrected.

When the material balance passes, the PSM may be executed.

A second material balance should be performed in accordance with 6.2.6 using the PSM output.


38

If the material balance fails, the source of the imbalance shall be identified and corrected.

When the material balance passes, the PSM may be re-executed.

Once validation is complete, PSM output theoretical quantities may be passed to the PMAS (refer to 6.1.4.4).

Figure 8: PSM Allocation Process

6.2.6 Output result validation The output of the PSM is the source theoretical quantities used by the PMAS to allocate end point quantities. The output of the PSM shall be validated with a material and energy balance with an emphasis on the mass balance of the phases (refer to Annex H).

PSM performance monitoring and reporting shall be incorporated into the PMAS performance monitoring and reporting program. (refer to API MPMS Chap. 20.1)

7 Multiphase and Wet Gas Flow Meter (MPFM) Configuration



39

7.1.1 General The operator shall be responsible for the development of a phase behavior application when phase behavior is used to determine MPFM configuration parameters. MPFM require accurate fluid definition as part of the overall meter configuration to function properly. This section provides a baseline procedure for the systematic development of fluid properties, the values of which serve as the PVT input parameters that reside in the meter configuration files. The operator can develop and manage the phase behavior application development or allow the MPFM vendor to determine the configuration parameter values.

When the configuration parameter values are vendor developed, the operator shall provide to the vendor, a laboratory PVT study (refer to 7.1.3.1), water density and volume factor, and other information as required by the vendor. The operator shall ensure that models and correlations developed by the vendor are applicable and valid for the fluids measured.

7.1.2 Phase behavior parameter definition: required outputs The output of the phase behavior application described in this Section shall become an integral part of the MPFM configuration parameters. The MPFM configuration parameters can include PVT and fluid properties at meter conditions and factors to convert these properties to reference conditions. In addition, meter technology specific fluid properties such as mass absorption coefficient and permittivity can be included. Refer to Table 10 for a categorized list of parameters.

Table 10: Typical PVT and fluid property configuration parameters

Category I Category II Category III

PVT and fluid properties at meter conditions

Gas density, 𝜌𝜌𝑔𝑔 Oil density, 𝜌𝜌𝑜𝑜 Water density, 𝜌𝜌𝑤𝑤 Gas viscosity, 𝜇𝜇𝑔𝑔 Oil viscosity, 𝜇𝜇𝑜𝑜 Gas/oil surface tension, 𝜏𝜏𝑔𝑔/𝑜𝑜

Conversion factors from meter to reference conditions

Gas volume factor, 𝐵𝐵𝑔𝑔 Oil volume factor, 𝐵𝐵𝑜𝑜 Water volume factor, 𝐵𝐵𝑤𝑤 Flash gas factor

Metering technology specific fluid properties

Gas, oil, and water permittivity Water conductivity NIR absorbance Mass absorption coefficient Speed of sound Cp/Cv (kappa)

NOTE: A significant portion of the configuration parameters are thermodynamic and physical properties specific to the fluids and the process conditions for the application. The former are often called PVT properties, while the latter may include viscosity, surface tension, etc. In addition, there are technology-specific parameters such as mass absorption coefficient, NIR absorbance, etc. These fluid properties have often been lumped together and called “PVT” properties.

7.1.3 Fluid characterization

7.1.3.1 PVT Study A full suite laboratory PVT study shall be used to develop PVT and fluid properties. The study shall include as a minimum: — initial reservoir pressure and temperature;

— saturation pressure at reservoir temperature;

— gas-oil ratio obtained from:

− single-stage flash to atmospheric conditions,


40

− differential liberation,

− multistage separator test;

— viscosity and density at reservoir conditions and saturation pressure at reservoir temperature;

— stock tank oil properties from:

− Single-stage flash to atmospheric conditions,

− Differential liberation,

− Multistage separator test;

— constant composition expansion test;

— differential liberation test (for black oil system);

— constant volume depletion test (for gas system);

— multistage separator test;

— standard conditions;

— reservoir fluid composition (single-phase);

— calculated properties of Cn+ fractions including molecular weight and density.

NOTE 1 The reservoir fluid composition provided in the PVT study report typically contains 30 or more well-defined components with the last component being a lumped fraction of C30+ or C36+. From an EOS phase behavior modeling purposes, the number of components used is reduced by the grouping of heavier fractions into PsC.

NOTE 2 Fluid densities at meter and reference conditions are a function of the process flow path. The multistage separator test in the PVT study is designed to mimic the separation stages during production operations.

7.1.3.2 Components This document does not prescribe a specific component set for this application. The selection of a component set should be based on factors including range and types of fluids, variation in composition, and the available PVT studies. The following properties and parameters should be defined for each component in the set:

— molecular weight (MW);

— Pc (critical pressure);

— Tc (critical temperature);

— Vc (critical volume);

— Tb (normal boiling point temperature);

— standard density;


41

— acentric factor;

— volume shift;

— binary interaction parameters;

— constituents of lumped PsC (as applicable).

The number of PsC shall be established during the development of this application. The number of PsC may be automated by the EOS software in the tuning process.

7.1.3.3 EOS The EOS shall be valid for the range of conditions applicable to the operation of the MPFM. This Standard does not prescribe a mathematical phase estimation method, EOS, or correlation. The EOS shall not include proprietary extensions or modifications. EOS that are open literature methods may be used.

Fluid property correlations may be used in place of EOS (refer to 7.1.3.5).

The functional specification shall document the type and precise version of the EOS used, including outside correlations and methods. A justification for the chosen EOS shall be included. Citations to published papers which document the EOS may be included. The goal is to ensure reproducibility and auditability.

For EOS model selection screening, the following process should be used:

Step 1: Select the Cn+ fraction to be used as a single PsC in the screening process. The Cn+ properties are reported along with the compositional analysis included in the PVT study.

Step 2: Tune the EOS to match saturation pressure at reservoir temperature.

Step 3: Select the EOS model that produced the best match with the saturation conditions.

The EOS shall be tuned against the test results from laboratory PVT study. The following should be identified prior to beginning the tuning process:

— target parameters from the PVT study tests;

— fitting and tuning parameters;

— limitations on fitting and tuning parameters;

— allowable relative deviation between EOS predicted and measured values.

The tuning process shall be documented as follows:

— list of PVT experiments including weighting factor;

— sequential tuning steps;

— list of tuning steps or actions defined by the modeler;

— list of tuning steps or actions automated by software;

— list of tuning and fitting parameters with values prior to tuning;

— values tuning and fitting parameters at the end of the tuning process;


42

— action relative deviation between EOS predicted and measured values.

A technical justification of the selected tuning and fitting parameters shall be documented.

Table 11 should be utilized as a tool to document the tuning process and model fidelity.

Table 11. Relative Deviation Between Laboratory Measured and EOS Predicted Reservoir Fluid Properties

Saturation Pressure @ T reservoir Measured EOS Predicted

Relative Deviation

(d)

Psat Gas-Oil Ratio (a) Single-stage flash Differential liberation (b) Multistage separator test Formation volume factor Bo) (c) @ P reservoir and T reservoir @ Psat and T reservoir

Measured EOS Predicted

Relative Deviation Measured EOS

Predicted Relative

Deviation Single-stage flash Differential liberation Multistage separator test

Reservoir fluid properties @ P reservoir and T reservoir @ Psat and T reservoir



Predicted Relative Deviation

Density Viscosity (e)

Stock tank oil properties °API Density @ STP



Predicted Relative

Deviation Single-stage flash Differential liberation Multistage separator test a Volume of gas liberated per volume of oil, both at standard conditions. b Constant volume depletion for gas systems. c Volume of oil at reservoir conditions per volume of oil at standard conditions. d EOS predicted minus laboratory measured divided by laboratory measured PVT value. e Common EOS modeling software have separate viscosity prediction models.

Table 12 should be used to document the tuning process and model fidelity.


43

Table 12. Relative Deviation Between Laboratory Measured and EOS Predicted Properties for Multistage Separator Test

P T GOR(a) Density(b) FVF(c)

Measured EOS-

Predicted

Relative Deviation

% Measured EOS-

Predicted

Relative Deviation

% Measured EOS-

Predicted

Relative Deviation

% Psat Tsat P1 T1 … … … … … … Po To

a Volume of gas liberated per unit oil volume, both at standard conditions b Oil density at pressure and temperature at each stage c Volume of oil at separator condition per unit volume of oil at standard conditions

7.1.3.4 Correlations Correlations may be used to determine PVT and fluid properties. While EOS models are better able to describe phase behavior of complex fluids such as retrograde condensate systems. Low GOR oils can be sufficiently modeled with simpler correlations like black oil model.

The MPFM vendor may provide proprietary correlations for the generation of technology specific parameters listed as Category III parameters in Table 10.

The correlations shall be valid for the range of conditions applicable to the operation of the MPFM. A correlation used to develop Category I and II configuration parameters shall not be proprietary. Correlations that are open literature methods may be used. The goal is to ensure reproducibility and auditability.

When correlations are used, the functional specification shall document the type and precise version of the correlations used. A justification for the chosen correlations shall be included. Citations to published papers which document the correlations may be included. For technology specific correlations the version control number and the parent MPFM software version shall be included.

7.1.4 Functional Specification 7.1.4.1 General A functional specification shall be developed and agreed to by the affected parties prior to placing the MPFM in service. The functional specification shall include key assumptions, descriptions, and design considerations for the determination of the configuration parameter values. The functional specification shall also include validation methods and acceptance criteria, and supporting information on EOS tuning, if applicable.

7.1.4.2 Process Flow Diagram (PFD) A PFD shall be included that describes the metering process from the MPFM location to the oil and gas export points. The PFD shall include the following:

— well identification and meter location;

— individual well fluid source (reservoir or zone);

— process flow path showing separation stages from the MPFM to reference conditions during normal operations;


44

— process flow path showing separation stages from the MPFM to reference conditions during well test/meter validation;

— MPFM minimum and maximum operating pressure and temperature;

— separation stages’ operating conditions for normal and well test operations;

— reference pressure and temperature.

The PFD shall be updated as necessary to reflect changes to the production process.

7.1.4.3 Simulation tools The type and precise version of the simulation software used, including EOS, correlations and methods and all applied settings shall be documented in the functional specification. Proprietary software not commercially available shall not be used.

7.1.4.4 Input data requirements The EOS model input composition set shall be derived from the laboratory PVT study. The number of components used may be reduced by the grouping of heavier fractions into PsC. The number and properties of PsC shall be defined by the modeler, automated by the EOS software, or determined as part of the tuning process.

For tuning purposes, reservoir pressure and temperature and other pertinent pressure and temperature data shall be used as input. The pertinent pressure and temperature data include pressure and temperatures used in the tests from the laboratory PVT study outlined in 7.1.3.1. For configuration parameter development, the input into the tuned model shall include:

— the MPFM minimum, maximum, and operating conditions;

— reference conditions;

— process stages of separation including minimum, maximum, and operating conditions;

— process stages of separation including minimum, maximum, and operating conditions for MPFM testing.

7.1.4.5 Output result requirements The EOS model outputs shall include the category I and category II parameters values required for the MPFM configuration. The category I parameters shall be stated at meter, stage, and reference conditions.

The output shall be presented to the MPFM vendor in a format compatible with the MPFM. This format can be in the form of the EOS model or a tabulated list of relevant parameters.

Input data used in the development of an EOS model or correlation set shall be provided to the vendor for inclusion in MPFM documentation as reference.

Configuration parameters specific to a metering technology shall be identified and listed separately from the PVT parameters.

The unit of measure and number of significant figures for each output property shall be included.



45

7.1.4.6 Validation and Acceptance Criteria The EOS validation methods, validation frequency, and acceptance criteria shall be established prior to implementation and documented in the functional specification.

All processes used to aid EOS validation, including methodologies for EOS tuning, shall be established prior to implementation, and documented in the functional specification.

The input composition validation methods and acceptance criteria shall be in accordance with Section 8 and established prior to implementation, and documented in the functional specification.


7.2.1 General The operator shall be responsible for the implementation of a phase behavior application when phase behavior is used to determine MPFM configuration parameters. Maintaining data quality are key to the MPFM performance while a systematic application of the phase behavior application facilitates repeatability and auditability. Implementation of the phase behavior application shall be in accordance with API MPMS Chap. 20.3.

7.2.2 Fluid characterization validation The relative deviation between the MPFM and separator measured rates in standard volumes are assessed against the established acceptable performance deviation or tolerance limit. If the relative phase rate deviations are outside the tolerance limit, i.e., non-conformant, then adjustment to the MPFM configuration may be required. Prior to making adjustment to PVT and fluid property configuration parameters, an assessment of non-fluid property related changes should be conducted.

The operator should implement a documented process to explore and determine the potential cause/s of non-conformance. The process should include operational changes as well as changes in reservoir conditions that may have caused validation failure. The following should be included in the assessment:

— Well test was conducted per API MPMS Ch. 20.5 – RP for Application of Production Well Testing in Measurement and Allocation;

— Capability assessment was performed on the single-phase reference meters to determine measurement uncertainty with the rates of the well to be tested;

— PVT properties used to convert separator volumetric rates to standard conditions have been validated;

— Well test process separation stages and operating conditions are per the functional specification;

— No reservoir related changes such as injected water breakthrough or reservoir pressure going below saturation has occurred since the last well test;

— No major flow regime changed has occurred since last well test;

— Starting of gas lift since last well test;

— Gas break thru when gas flooding since last well test;

— Major Change in operating pressure since the last well test;

— Change to zonal mix since the last well test.


46

If none of the above applies, then the EOS model should be reviewed per the Validation and Acceptance Criteria in 7.1.4.6. The acceptance criteria for the EOS model may have to be revisited. The weighting factors of PVT input data used in the original EOS model development may also be adjusted.

7.2.3 Simulation tool validation An overall material and energy balance (refer to Annex H) shall be performed as outlined in the functional specification. Errors between individual theoretical quantities, energy content, and end point data indicate problems related to measurement, fluid characterization, or EOS. A material and energy balance is a tool that can facilitate troubleshooting and problem resolution.


7.2.4.1 Composition input data validation Laboratory oversight and auditing shall be conducted on a periodic basis and as part of the operation of the PMAS when MPFM are used in a PMAS. (refer to API MPMS Chap. 20.1)



7.2.4.2 Process input data validation The specified application input process data shall be reviewed for accuracy prior to use in a simulation model.

NOTE Temperature, pressure, and flow measurements might exhibit high uncertainties that can adversely affect the input process data for the MPFM.


— the operator shall verify that the samples are taken per API MPMS Chapter 20.3.


— temperature and pressure data representative of the meter operating range

— temperature and pressure data of the process stages of separation from meter to reference conditions

— Properties obtained from PVT study representative of expected pressure, temperature, and composition

— The operator shall document any change or omission of data from the simulation model.

7.2.5 Output result determination The category I and category II parameters values obtained from the simulation model shall be valid over the expected operating range.

The simulation tool should serve two purposes:

— interpolation of PVT properties (Category I parameters) to match current meter operating conditions,


47

— establish category II parameters at established reference conditions as a result of process separation conditions from meter to process conditions

Figure 9 below illustrates the step by step process to serve these two purposes.

Figure 9: Application of phase behavior in developing MPFM configuration parameters

7.2.6 Output result validation The output of the simulation model is the source of category I and category II configuration parameters used by the MPFM to determine measurement quantities at the meter condition. The output of the EOS model shall be validated against criteria as established in 7.1.4.5.

8 Fluid Sample and PVT Fluid Property Quality Assurance (QA)


8.1.1 General The operator shall be responsible for the development of a fluid sample and PVT fluid property quality assurance process for phase behavior applications in upstream measurement and allocation. Representative fluid properties are critical to predicting phase behavior and the outcome of its application.


48

It is also critical that fluid compositions are properly represented. This Section addresses the development of QA tools and methods.

8.1.2 Phase behavior parameter definition: required outputs The QA tool shall be applicable to the range of fluid types and process conditions covered by the phase behavior application in which it is used (base application). When applied in an allocation related process, the QA shall be capable of constant update due to the periodic nature of allocation processes.

The QA output shall include indication as to where fluid compositions and properties fall relative to acceptance criteria established for the phase behavior application.


8.1.3.1 Measurements and PVT studies For allocation applications, see 5.1.3.1, 6.1.3.1

For measurement applications, see 7.1.3.1, 8.1.3.1

8.1.3.2 Components The QA application shall use the same component set, properties, and parameters used in the base application.

8.1.3.3 EOS The QA application shall use the same EOS, if applicable, used by the base application. The QA application may use additional EOS and correlations for comparison purposes.

8.1.3.4 Correlations The QA application shall use the same correlations, if applicable, used by the base application. The QA application may use additional EOS and correlations for comparison purposes.

8.1.4 Functional specification

8.1.4.1 General The base application functional specification shall incorporate key assumptions, descriptions, and design considerations used in the development of the QA application.

8.1.4.2 Process description A flowchart, with descriptions, that illustrates the QA process followed in the QA application shall be included. The flowchart shall include the following: — Inputs

— Steps

— Decisions

— Outputs

8.1.4.3 Simulation tools The type and precise version of the simulation software used, including EOS, correlations and methods, and all applied settings shall be documented in the functional specification of the base application. Proprietary software not commercially available shall not be used.


49

8.1.4.4 Input data requirements The input data shall be the subject fluid compositional and fluid property data from the phase behavior application.

Additionally, data necessary for the specific QA process shall be included.

8.1.4.5 Output result requirements The QA application output should contain the input sample and PVT parameters, their corresponding check values, and an error percentage for the checked values. In addition, an indication of a fail condition should be included.

8.1.4.6 Validation and Acceptance Criteria The QA application validation methods, validation frequency, and acceptance criteria shall be established prior to implementation, and documented in the functional specification.

All processes used to aid QA validation, including methodologies for EOS tuning, shall be established prior to implementation, and documented in the functional specification.

Fluid quality confirmation documentation that describes all QA application fluid quality related information and activities shall be provided. This documentation should clearly identify the frequency of activities, all specifically cited reference standards, along with fluid quality validation parameters and associated acceptance criteria (refer to API MPMS Chap. 20.1).


8.2.1 General The application of PVT quality assurance shall be conducted in accordance with the requirements and recommendations of the base application. Refer to 5.2, 6.2, 7.2, or 9.2, as applicable for guidance.

9 Flow Modeling (Virtual Flow Metering)


9.1.1 General The operator shall be responsible for the development of a phase behavior application when phase behavior is used to determine VFM configuration parameters. VFM require accurate fluid definition as part of the overall meter configuration to function properly. This section provides a baseline procedure for the systematic development of fluid properties, the values of which serve as the PVT input parameters that will reside in the meter configuration files.

9.1.2 Phase behavior parameter definition: required outputs The VFM fluid properties shall be provided in tabular format covering pressures and temperatures ranging from reservoir to reference conditions. The VFM vendor may specify a different format and range. The fluid properties should include as a minimum:

— equilibrium fraction of gas/liquid/water;

— gas density;

— liquid density;

— gas/liquid surface tension;


50

— gas mass fraction;

— enthalpy;

— gas viscosity;

— liquid viscosity.


9.1.3.1 PVT Study A full suite laboratory PVT study shall be used to develop PVT and fluid properties. The study shall include as a minimum: — initial reservoir pressure and temperature;

— saturation pressure at reservoir temperature;

— gas-oil ratio obtained from:

− single-stage flash to atmospheric conditions,

− differential liberation,

− multistage separator test;

— viscosity and density at reservoir conditions and saturation pressure at reservoir temperature;

— stock tank oil properties from:

− Single-stage flash to atmospheric conditions,

− Differential liberation,

− Multistage separator test;

— constant composition expansion test;

— differential liberation test (for black oil system);

— constant volume depletion test (for gas system);

— multistage separator test;

— standard conditions;

— reservoir fluid composition (single-phase);

— calculated properties of Cn+ fractions including molecular weight and density.

NOTE 1 The reservoir fluid composition provided in the PVT study report typically contains 30 or more well-defined components with the last component being a lumped fraction of C30+ or C36+. From an EOS phase behavior modeling purposes, the number of components used is reduced by the grouping of heavier fractions into PsC.


51

NOTE 2 Fluid densities at meter and reference conditions are a function of the process flow path. The multistage separator test in the PVT study is designed to mimic the separation stages during production operations.

9.1.3.2 Components This document does not prescribe a specific component set for this application. The selection of a component set should be based on factors including range and types of fluids, variation in composition, and the available PVT studies. The following properties and parameters should be defined for each component in the set:

— molecular weight (MW);

— Pc (critical pressure);

— Tc (critical temperature);

— Vc (critical volume);

— Tb (normal boiling point temperature);

— standard density;

— acentric factor;

— volume shift;

— binary interaction parameters;

— constituents of lumped PsC (as applicable).

The number of PsC shall be established during the development of this application. The number of PsC may be automated by the EOS software in the tuning process.

9.1.3.3 EOS The EOS shall be valid for the range of conditions applicable to the operation of the VFM. This Standard does not prescribe a mathematical phase estimation method, EOS, or correlation. The EOS shall not include proprietary extensions or modifications. EOS that are open literature methods may be used.

AGA-8 or GERG 2008 should be used as the basis for gas density.

Fluid property correlations may be used in place of EOS in accordance with 9.1.3.4. A volume shift or corresponding states method should be used for the determination of liquid density.

The functional specification shall document the type and precise version of the EOS used, including outside correlations and methods. A justification for the chosen EOS shall be included. Citations to published papers which document the EOS may be included. The goal is to ensure reproducibility and auditability.

For EOS model selection screening, the following process should be used:

Step 1: Select the Cn+ fraction to be used as a single PsC in the screening process. The Cn+ properties are reported along with the compositional analysis included in the PVT study.

Step 2: Tune the EOS to match saturation pressure at reservoir temperature.

Step 3: Select the EOS model that produced the best match with the saturation conditions.


52

The EOS shall be tuned against the test results from laboratory PVT study. The following should be identified prior to beginning the tuning process:

− target parameters from the PVT study tests,

− fitting and tuning parameters,

− limitations on fitting and tuning parameters, and

− allowable relative deviation between EOS predicted and measured values.

The tuning process shall be documented as follows:

− list of PVT experiments including weighting factor,

− sequential tuning steps,

− list of tuning steps or actions defined by the modeler,

− list of tuning steps or actions automated by software,

− list of tuning and fitting parameters with values prior to tuning,

− values tuning and fitting parameters at the end of the tuning process,

− action relative deviation between EOS predicted and measured values.

A technical justification of the selected tuning and fitting parameters shall be documented.

Table 13 should be utilized as a tool to document the tuning process and model fidelity.


53

Table 13. Relative Deviation Between Laboratory Measured and EOS Predicted Reservoir Fluid Properties

Saturation Pressure @ T reservoir Measured EOS Predicted

Relative Deviation

(d)

Psat Gas-Oil Ratio (a) Single-stage flash Differential liberation (b) Multistage separator test Formation volume factor Bo) (c) @ P reservoir and T reservoir @ Psat and T reservoir



Predicted Relative

Deviation Single-stage flash Differential liberation Multistage separator test

Reservoir fluid properties @ P reservoir and T reservoir @ Psat and T reservoir



Predicted Relative Deviation

Density Viscosity (e)

Stock tank oil properties °API Density @ STP



Predicted Relative

Deviation Single-stage flash Differential liberation Multistage separator test a Volume of gas liberated per volume of oil, both at standard conditions. b Constant volume depletion for gas systems. c Volume of oil at reservoir conditions per volume of oil at standard conditions. d EOS predicted minus laboratory measured divided by laboratory measured PVT value. e Common EOS modeling software have separate viscosity prediction models.

Table 14 should be used to document the tuning process and model fidelity.

Table 14. Relative Deviation Between Laboratory Measured and EOS Predicted Properties for Multistage Separator Test

P T GOR(a) Density(b) FVF(c)

Measured EOS-

Predicted

Relative Deviation

% Measured EOS-

Predicted

Relative Deviation

% Measured EOS-

Predicted

Relative Deviation

% Psat Tsat P1 T1 … … … … … … Po To

a Volume of gas liberated per unit oil volume, both at standard conditions b Oil density at pressure and temperature at each stage c Volume of oil at separator condition per unit volume of oil at standard conditions


54

9.1.3.4 Correlations Correlations may be used to determine PVT and fluid properties. While EOS models are better able to describe phase behavior of complex fluids such as retrograde condensate systems. Low GOR oils can be sufficiently modeled with simpler correlations like black oil model.

The correlations shall be valid for the range of conditions applicable to the operation of the VFM. Correlations shall not be proprietary. Correlations that are open literature methods may be used. The goal is to ensure reproducibility and auditability.

When correlations are used, the functional specification shall document the type and precise version of the correlations used. A justification for the chosen correlations shall be included. Citations to published papers which document the correlations may be included. For technology specific correlations the version control number and the parent VFM software version shall be included.


9.1.4.1 General A functional specification shall be developed and agreed to by the affected parties prior to placing the VFM in service. The functional specification shall include key assumptions, descriptions, and design considerations for the determination of the configuration parameter values. The functional specification shall also include validation methods and acceptance criteria, and supporting information on EOS tuning, if applicable.

9.1.4.2 Process Flow Diagram (PFD) A PFD shall be included that describes the metering process from the VFM location to the oil and gas export points. The PFD shall include the following:

— well identification and meter location;

— individual well fluid source (reservoir or zone);

— process flow path showing separation stages from the VFM to reference conditions during normal operations;

— process flow path showing separation stages from the VFM to reference conditions during well test/meter validation;

— VFM minimum and maximum operating pressure and temperature;

— separation stages’ operating conditions for normal and well test operations;

— reference pressure and temperature.

The PFD shall be updated as necessary to reflect changes to the production process.

9.1.4.3 Simulation tools The type and precise version of the simulation software used, including EOS, correlations and methods and all applied settings shall be documented in the functional specification. Proprietary software not commercially available shall not be used.

9.1.4.4 Input data requirements The EOS model input composition set shall be derived from the laboratory PVT study. The number of components used may be reduced by the grouping of heavier fractions into PsC. The number and


55

properties of PsC shall be defined by the modeler, automated by the EOS software, or determined as part of the tuning process.

For tuning purposes, reservoir pressure and temperature and other pertinent pressure and temperature data shall be used as input. The pertinent pressure and temperature data include pressure and temperatures used in the tests from the laboratory PVT study outlined in 9.1.3.150. For configuration parameter development, the input into the tuned model shall include:

— the VFM minimum, maximum, and operating conditions;

— well zone ratios;

— reference conditions;

— process stages of separation including minimum, maximum, and operating conditions;

— process stages of separation including minimum, maximum, and operating conditions for VFM testing.

9.1.4.5 Output result requirements The EOS model outputs shall include the properties outlined in 9.1.2, stated at meter, stage, and reference conditions.

The output data should be smoothed to perform well in the VFM algorithms.

The output shall be presented to the VFM vendor in a format compatible with the VFM. This format can be in the form of the EOS model or a tabulated list of relevant parameters.

Input data used in the development of an EOS model or correlation set shall be provided to the vendor for inclusion in VFM documentation as reference.

Configuration parameters specific to a metering technology shall be identified and listed separately from the PVT parameters.

The unit of measure and number of significant figures for each output property shall be included.


9.1.4.6 Validation and Acceptance Criteria The EOS validation methods, validation frequency, and acceptance criteria shall be established prior to implementation and documented in the functional specification.

All processes used to aid EOS validation, including methodologies for EOS tuning, shall be established prior to implementation, and documented in the functional specification.

Typically, the sum of VFM’s are compared to an available fiscal meter. The VFM should be able to simulate historical data. Single phase disparities are usually because the hydrocarbon composition is shifting or water cut is uncertain and the fluid characterization should be reevaluated. If phase ratios are accurate but overall rate is inaccurate the hydrodynamic model and thermophysical properties should be reevaluated.

The input composition validation methods and acceptance criteria shall be in accordance with Section 8 and established prior to implementation and documented in the functional specification.


56


9.2.1 General The operator shall be responsible for the implementation of a phase behavior application when phase behavior is used to determine hydrodynamic and thermophysical properties used in the VFM to determine mass flowrate. Maintaining data quality are key to the VFM performance while a systematic application of the phase behavior application facilitates repeatability and auditability. Implementation of the phase behavior application shall be in accordance with API MPMS Chap. 20.5.

9.2.2 Fluid characterization validation The relative deviation between the VFM and separator measured rates in standard volumes are assessed against the established acceptable performance deviation or tolerance limit. If the relative phase rate deviations are outside the tolerance limit, i.e., non-conformant, then adjustment to the MPFM configuration may be required. Prior to making adjustment to PVT and fluid property configuration parameters, an assessment of non-fluid property related changes should be conducted.

The operator should implement a documented process to explore and determine the potential cause/s of non-conformance. The process should include operational changes as well as changes in reservoir conditions that may have caused validation failure. The following should be included in the assessment:

— Well test was conducted per API MPMS Ch. 20.5 – RP for Application of Production Well Testing in Measurement and Allocation;

— Capability assessment was performed on the single-phase reference meters to determine measurement uncertainty with the rates of the well to be tested;

— PVT properties used to convert separator volumetric rates to standard conditions have been validated;

— Well test process separation stages and operating conditions are per the functional specification;

— No reservoir related changes such as injected water breakthrough or reservoir pressure going below saturation has occurred since the last well test;

— No major flow regime changed has occurred since last well test;

— Starting of gas lift since last well test;

— Gas break thru when gas flooding since last well test;

— Major Change in operating pressure since the last well test;

— Change to zonal mix since the last well test.

If none of the above applies, then the EOS model should be reviewed per the Validation and Acceptance Criteria in 9.1.4.6. The acceptance criteria for the EOS model may have to be revisited. The weighting factors of PVT input data used in the original EOS model development may also be adjusted.

9.2.3 Simulation tool validation An overall material and energy balance (refer to Annex H) shall be performed as outlined in the functional specification. Errors between individual theoretical quantities, energy content, and end point data indicate problems related to measurement, fluid characterization, or EOS. A material and energy balance is a tool that can facilitate troubleshooting and problem resolution.


57



The reported compositional analyses’ conditions shall match the source conditions at the time the sample was taken. For samples taken at a liquid/gas separation point, the source conditions shall mean the pressure and temperature of the separator. The flash ratio resulting from the sample composition sample should be within expected thresholds.


9.2.4.2 Process input data validation The specified application input process data shall be reviewed for accuracy prior use in a simulation model.



— temperature and pressure data representative of the VFM operating range;

— temperature and pressure data representative of the process stages of separation from VFM to reference conditions; and

— Properties obtained from PVT study representative of expected pressure, temperature and composition.

— The operator shall document any change or omission of data from the simulation model.

9.2.5 Output result determination The VFM parameter values obtained from the simulation model shall be valid over the expected operating range.

The simulation tool should serve two purposes:

— interpolation of PVT properties to current meter condition,

— interpolation of properties at established reference conditions as a result of process separation conditions from meter to process conditions.

Figure 10 below illustrates the step by step process to serve these two purposes.


58

Figure 10: Application of phase behavior in developing VFM thermophysical properties

9.2.6 Output result validation The output of the simulation model is the source of VFM parameters and used to determine mass flowrates at the meter conditions. The output of the EOS model shall be validated against criteria as established in 9.1.4.5.

10 PVT Fluid Property Interpolation to Alternate Process Conditions


10.1.1 General Separator liquid and gas compositional analyses represent the phase compositions of a source stream at separator pressure and temperature when the samples were taken. When applied at alternate conditions, the phase compositions shall be interpolated to the alternate pressure and temperature in a conditioning process. The conditioning process includes recombining the liquid and gas streams in an EOS model and separating them at the desired conditions to yield phase compositions applicable to the alternate conditions.


59


10.1.2.1 Conditioning without mass conservation When the desired output is compositional only, the conditioning process may be performed with an approximate gas quantity to liquid quantity ratio. The conditioning shall include valid liquid and gas compositional data that are in equilibrium at the sampling conditions.

The output from this conditioning should not be used to represent the actual separator incoming stream composition or for the determination of alternate gas and liquid quantities at alternate conditions.

10.1.2.2 Conditioning with mass conservation When the desired output is actual incoming stream composition or alternate gas and liquid quantities at alternate conditions, the conditioning process shall be performed using a rigorous determination of the gas quantity to liquid quantity ratio. This conditioning shall also include valid liquid and gas compositional data that are in equilibrium at the sampling conditions.


10.1.3.1 Measurement The following is a list of field and laboratory data that should be used in the conditioning process:

— Laboratory Liquid composition

— Laboratory Gas composition

— Separator pressure and temperature at sampling conditions

— Separator pressure and temperature at alternate conditions

— Gas flow rate or volume at the time of sampling

— Oil flow rate or volume at the time of sampling

If the compositions are used in an application that requires tuning, the laboratory compositions shall be processed using the application’s tuning process. Additional laboratory data that may be used includes:

— non-discrete component MW and liquid density

— fluid MW and liquid density

— liquid shrinkage factor

— liquid flash gas factor

— liquid flash gas composition

10.1.3.2 Component set The component set shall match the component set for the application using the conditioned compositions. When there is no governing application, guidance found in 5.1.3.2 should be followed.

10.1.3.3 EOS The EOS used shall match the EOS for the application using the conditioned compositions. When there is no governing application, guidance found in 5.1.3.3 should be followed.


60

10.1.4 Functional specification

10.1.4.1 General Methodology, correlations, equations of state, compositions and other pertinent information related to the reconditioning of samples shall be documented in the functional specification.

10.1.4.2 Process description The process description shall include:

— Separator identification;

— Pressure instrumentation identification;

— Temperature instrumentation identification;

— Source of gas quantity value;

— Source of liquid quantity value;

10.1.4.3 Simulation tools The conditioning function may be built into the base application. Alternatively, the conditioning tool may be built in the same process simulation software as the governing application using the same EOS, outside correlations and methods and applied settings.

When there is no governing application, guidance found in 5.1.4.2 should be followed.

Figure 11 below contains an example of a composition conditioning tool.

Figure 11: Example composition conditioning tool

Where:

Qgas is the gas quantity value gathered in conjunction with the gas sample;

Cg1 is the composition of the gas sample;

Qliq is the liquid quantity value gathered in conjunction with the liquid sample;

Cl1 is the composition of the liquid sample;

P1 is the pressure of the sample pair;


61

T1 is the temperature of the sample pair;

P2 is the new pressure for conditioned sample pair;

T2 is the new temperature for conditioned sample pair;

Cg2 is the resulting gas composition;

Cl2 is the resulting liquid composition.

10.1.4.4 Input data requirements The input data used shall be a complete set of characterized liquid and gas compositions including PsC properties used as well as the representative Gas-Oil Ratio.

The liquid and gas compositions shall be determined from samples taken at the same time. The separation pressure and temperature shall be recorded from separator instrumentation. Sampling pressure and temperature shall not be used if different than separation pressure.

10.1.4.5 Output result requirements Output results shall consist of the recalculated vapor and liquid combinations at the new process conditions. These new combinations shall be included in the functional specification. Table 15 below contains example conditioning tool output.

Table 15: Example conditioning output Gas

Mol % Liq

Mol%

Nitrogen

Methane

Carbon dioxide

Ethane

Propane

Isobutane

n-Butane

Isopentane

n-Pentane

PsC1

PsC2

PsC3

10.1.4.6 Validation and acceptance criteria As with sample validation, allocation KPIs may be used to determine the accuracy of many assumptions made during the allocation, including composition. As the output derived in 10.1.4.4 is by definition, in ideal VLE, a K-plot sample validation are not applicable. Any errors attributed to sample quality are attributed to unrepresentative operating conditions, operational abnormalities (such as gas carryover/carry under) or initial sample composition and indicate that a new sample should be obtained.



62

10.2.1 General The application of PVT Fluid Property interpolations shall be conducted in accordance with the requirements and recommendations of the base phase behavior application Refer to 5.2, 6.2, 7.2, or 8.2, as applicable for guidance.

11 Performance Management

11.1 General Confidence in applied phase behavior performance is important in upstream measurement. Managing phase behavior applications in upstream measurement requires routine review of fluid characterizations, phase behavior model specifications and predictions, incorporation of all applicable process changes, continuous monitoring and reporting of KPIs, and a systematic framework that identifies and resolves out-of-tolerance phase behavior performance.

11.2 Functional Specification Review A complete phase behavior application functional specification review shall be performed at minimum once a year. The review shall consist of:

— a comparison of assumptions, fluid characterizations, simulation tools, input and output specifications, validation methods, and performance acceptance criteria used in the phase behavior application against the documented functional specification;

— an assessment of assumptions, fluid characterizations, simulation tools, input and output specifications, validation methods, and performance acceptance criteria used in the phase behavior application against current process conditions for applicability.

All discrepancies identified in the phase behavior functional specification review shall be documented.

11.3 Functional Specification Modifications All applicable phase behavior application modifications shall be documented in the functional specification. This includes changes resulting from:

— technically justified modifications identified during the functional specification review;

— major process changes impacting the phase behavior application (e.g. new inputs or outputs).

A management of change documentation process should be used to document:

— the functional specification change;

— the original functional specification;

— the reason for the change,

— the demonstrated impact of the change (e.g. a simulation software update can introduce slightly different outputs). This can require several data points where the modified phase behavior application is executed in parallel with the unmodified application.

Functional specification modifications shall be communicated to affected parties. Prior to implementing modifications, a technical review committee among the affected parties should review the proposed modifications.


63

11.4 Validation and Reproducibility of Results For phase behavior applications used in production measurement and allocation systems (refer to API MPMS Ch. 20.1), at least one method of validation for fluid characterization, simulation tools (if specified), inputs and outputs shall be performed with each allocation.

Validation of fluid characterization, simulation tools (if specified), inputs and outputs shall be performed with any major process change (e.g. introduction or change in fluids; added/subtracted production processing) and documented in the functional specification.

Documentation supporting the functional specification and validation of fluid characterization, simulation tools (if specified), inputs and outputs necessary to reliably reproduce output results shall be made accessible to affected parties.

11.5 Performance Monitoring and Reporting KPIs should be established to assist in monitoring phase behavior application performance. KPIs can include the following:

— comparison of phase behavior application outputs against actual measured quantities (e.g. fluid properties; hydrocarbon quantities);

— phase behavior application inputs and outputs acceptance or rejection rates;

— changes in process conditions (e.g. flow volumes, fluid types, pressures, temperatures).

For each KPI, out-of-tolerance limits should be established.

KPIs and any deviations beyond the out-of-tolerance limits should be reported in a manner agreed to by the affected parties.

11.6 Out-of-tolerance Performance Management A documented process should be developed for managing out-of-tolerance performance. The process should include:

— out-of-tolerance incident tracking, reporting and resolution;

— identification of out-of-tolerance root causes;

— recommendations and resolution of out-of-tolerance events;

— updates to the phase behavior application functional specification if required;

— re-validation of the phase behavior application if required;

— reporting to affected parties and shared lessons learned.


64

Annex A (informative)

Process Description Examples The following examples are for illustration purposes only. They are not to be considered exclusive or exhaustive in nature. API makes no warranties, express or implied for reliance on or any omissions from the information contained in this document.

EXAMPLE 1 Process Flow Diagram used in a phase behavior application


65

Annex B (informative)

Comprehensive Compositional Component List Determination Example

The following examples are for illustration purposes only. They are not to be considered exclusive or exhaustive in nature. API makes no warranties, express or implied for reliance on or any omissions from the information contained in this document.

Using a comprehensive component list, as depicted in Annex B, can minimize the need for EOS tuning. In addition, using only one pseudo-component (e.g. C11+) can minimize the EOS tuning requirements.

A typical GPA 2261 [13] hexanes plus (C6+) analysis contains a component list of basic hydrocarbon molecules starting with methane through n-pentane including the nonhydrocarbons nitrogen and carbon dioxide. The remaining hydrocarbons, hexanes and larger, are grouped together as a hexanes plus component (refer to Table B.1). Some analyses (C7+) will further break out hexanes as a separate component group with heptanes plus representing the remaining hydrocarbons (refer to Table B.2). Hexanes could be the normal paraffin n-hexane or hexanes, all six carbon hydrocarbons including isomers, cyclics, aromatics, etc. Components are typically reported in molar and weight percentages.

Table B.1 C6+ component list Component Mol % Wt %

Nitrogen Methane

Carbon dioxide

Ethane

Propane

Isobutane

n-Butane

Isopentane

n-Pentane

Hexanes plus


66

Table B.2 C7+ component list Component Mol % Wt %

Nitrogen Methane

Carbon dioxide

Ethane

Propane

Isobutane

n-Butane

Isopentane

n-Pentane

Hexanes

Heptanes plus

These component sets are often supplied with additional data that are derived from calculations performed using these percentages and from other analytical methods applied to the samples. These calculations and analytical methods are typically performed to some industry standard. The data for liquids can include:

— component liquid volume percent,

— specific gravity of live and dead fluids,

— API gravity or density,

— MW,

— shrinkage factor,

— MW of C+ component,

— density of C+ component,

— flash factor,

— flash gas density,

— flash gas MW,

— flash gas gross heating value,

— sample pressure and temperature.


67

The data for gas can include:

— component molar percent,

— component weight percent,

— component gallons per MSCF (GPM),

— relative density, real and ideal,

— compressibility,

— gross heating value saturated–real and ideal,

— gross heating value dry–real and ideal,

— sample pressure and temperature.

For basic allocations, the allocator generally relies on this additional data rather than the molar and weight percentages to perform an allocation. Factors such as shrinkage, flash and heating values are applied to source quantities to determine theoretical quantities for that source at an end point.

For allocations using an EOS model, the molar compositions become the critical data from the analyses. The additional compositional data required is usually limited to pressure, temperature, and liquid molecular weight and density. Other data may be useful in simulation model tuning and validation.

Whereas the C6+ and C7+ analyses worked well for basic allocations, these analyses often do not adequately define a fluid for use in an EOS model. With all hydrocarbons, hexane and larger, grouped into a single component with a single set of properties, it is difficult to have an EOS accurately calculate liquid volume shrinkage, flash gas volume, and flash gas energy. The C6+ or C7+ molecules will tend to stay in liquid through the simulated process, understating oil shrinkage and flash gas volume and energy. EOS modelers typically break these C+ components into multiple PsC so that, amongst other things, component distribution more accurately calculates these fluid properties. The list can look like this:

— nitrogen — n-pentane,

— methane, — pseudo hexane,

— carbon dioxide, — pseudo 1,

— ethane, — pseudo 2,

— propane, — pseudo 3,

— isobutane, — pseudo 4,

— n-butane, — pseudo 5.

— isopentane,

The PsC are generated from the components making up the C+ component. To obtain the compositional make-up of the C+ component, an extended analyses or correlations are used.

Because allocations using phase behavior can involve multiple streams of dissimilar fluids with changing compositional make up from one allocation period to the next, it is not likely that PsC can be developed that can be used across production streams or even across allocation periods. The need to generate multiple PsC for multiple streams for each allocation period can become overwhelming for an allocator given the


68

time constraints dictated by the availability of compositional and volume data relative to the requirement to timely report allocated production.

To obtain adequate EOS results in a timely manner, an allocator can use an extended analysis with component groupings according to carbon number. By extending out to C10+, C11+, or C12+, the allocator gets a better definition of the fluid and avoids a PsC in the gas streams. This also eliminates the need to define a GHV for a PsC. Typically, the normal paraffin molecule of the carbon group acts as a surrogate to represent the group.

Commercial simulation software is available with component libraries containing predefined properties. It is not necessary for the allocator to define them. Also, this surrogate approach lends itself to repeatability and audit.

The same commercial software can generate a completely defined PsC with estimated properties given some information such MW and liquid density. To minimize the need for EOS tuning, it is useful to limit the number of PsC. Typically, the MW and liquid density of the C+ component is used or the PsC MW, and liquid density is derived from the total fluid MW and liquid density. Table B.3 contains a component list with these component groups and surrogates.

Table B.3: Decanes Plus (C10+) Component List Component/Component Group Surrogate

Nitrogen Nitrogen

Carbon dioxide Carbon dioxide

Methane Methane

Ethane Ethane

Propane Propane

Iso-butane Iso-butane

n-Butane n-Butane

Iso-pentane Iso-pentane

n-Pentane n-Pentane

C6 Hexanes n-Hexane

C7 Heptanes n-Heptane

C8 Octanes n-Octane

C9 Nonanes n-Nonane

Decanes and heavier Pseudo (C10+)


69

Although an improvement, the allocator may find that further definition is needed. In this case, an extended analysis such as one found in GPA 2286[14] can be used to generate the following component list:

— isopentane, — methylcyclohexane,

— n-pentane, — trimethylcyclopentanes,

— neohexane, — toluene,

— 2-methylpentane, — 2-methylheptane,

— 3-methylpentane, — 3-methylheptane,

— n-hexane, — dimethylcyclohexanes,

— methylcyclopentane, — n-octane,

— benzene, — C8 aromatics,

— cyclohexane, — C9 naphthenes,

— 2-methylhexane, — C9 paraffins,

— 3-methylhexane, — n-nonane,

— dimethylcyclopentanes, — decanes+.

— n-heptane,

This component list is more representative of the various components within the carbon number group. Table B.4, Table B.5, Table B.6, and Table B.7 contain breakouts of the C6, C7, C8, and C9 groups from this list, respectively.

Table B.4: C6 Components and Properties

Component

Formula Molar Mass

Boiling Point

°F

Relative Density

Critical Pressure

psia

Critical Temp.

°F

Critical Volume ft3/lbm

Acentric Factor

Neohexane C6H14 86.18 121.5 0.6542 449.6 420.5 0.0665 0.2341

2-Methylpentane C6H14 86.18 140.4 0.6584 440.9 436.2 0.0684 0.2803

3-Methylpentane C6H14 86.18 146.2 0.6695 452.5 448.6 0.0684 0.2736

n-Hexane C6H14 86.18 155.7 0.6640 436.9 453.8 0.0684 0.2996

Methylcyclopentane C6H12 84.16 161.3 0.7541 549.7 499.2 0.0605 0.2281

Benzene C6H6 78.11 176.1 0.8852 710.0 552.0 0.0525 0.2097

Cyclohexane C6H12 84.16 177.4 0.7840 591.8 537.2 0.0586 0.2091


70


Component

Formula Molar Mass

Boiling Point

°F

Relative Density

Critical Pressure

psia

Critical Temp.

°F


Acentric Factor

2-Methylhexane C7H16 100.20 194.0 0.6838 397.4 495.1 0.0673 0.3302

3-Methylhexane C7H16 100.20 197.3 0.6922 407.6 503.7 0.0646 0.3228

Dimethylcyclopentanes* C7H14 98.19 190.1 0.7592 493.1 524.9 0.0609 0.2653

n-Heptane C7H16 100.20 209.1 0.6992 396.8 512.6 0.0684 0.3498

Methylcyclohexane C7H14 98.19 213.7 0.7744 504.7 570.1 0.0602 0.2370

Toluene C7H8 92.14 231.1 0.8723 595.8 605.5 0.0549 0.2642

* Represents a component group.


Component

Formula Molar Mass

Boiling Point

°F

Relative Density

Critical Pressure

psia

Critical Temp.

°F


Acentric Factor

2-Methylheptane C8H18 114.23 243.8 0.7027 362.6 547.8 0.0684 0.3803

3-Methylheptane C8H18 114.23 246.1 0.7105 369.8 554.8 0.0651 0.3714

Dimethylcyclohexanes* C8H16 112.22 247.3 0.7856 459.8 594.2 0.0595 0.3065

n-Octane C8H18 114.23 258.1 0.7066 360.7 564.2 0.0690 0.3994

C8 Aromatics* C8H10 106.17 277.1 0.8722 523.4 651.2 0.0564 0.3033



Component

Formula Molar Mass

Boiling Point

°F

Relative Density

Critical Pressure

psia

Critical Temp.

°F


Acentric Factor

C9 Naphthenes* C9H18 126.24 277.9 0.7834 417.0 642.1 0.0596 0.3920

C9 Paraffins* C9H20 128.26 271.1 0.7150 340.8 578.4 0.0654 0.4580

n-Nonane C9H20 128.26 303.4 0.7222 330.8 610.5 0.0693 0.4453


From Table B.4, Table B.5, Table B.6, and Table B.7, it can be seen that there is still a disparity of properties within a carbon number group. For greater definition, the allocator can subdivide the component groups into alkanes, naphthenes, and aromatics while still using the standard extended analysis component list. Again, the allocator can assign surrogates rather than developing multiple PsC for each process stream. Table B.8, Table B.9, Table B.10, and Table B.11show the groupings and a suggested surrogate component for each subgroup.


71

Table B.8: C6 Alkanes, Naphthenes, and Aromatics and Their Surrogates

Component Formula Molar Mass Relative Density HHV Btu/scf

Surrogate

C6 Alkanes

Neohexane C6H14 86.18 0.6542 4735.8

n-Hexane 2-Methylpentane C6H14 86.18 0.6584 4747.2

3-Methylpentane C6H14 86.18 0.6695 4750.2

n-Hexane C6H14 86.18 0.6640 4755.9

C6 Naphthenes

Methylcyclopentane C6H12 84.16 0.7541 4500.5 Cyclohexane

Cyclohexane C6H12 84.16 0.7840 4481.2

C6 Aromatics

Benzene C6H6 78.11 0.8852 3741.5 Benzene


Component Formula Molar Mass Relative Density HHV Btu/scf

Surrogate

C7 Alkanes

2-Methylhexane C7H16 100.20 0.6838 5494.3

n-Heptane 3-Methylhexane C7H16 100.20 0.6922 5498.1

n-Heptane C7H16 100.20 0.6992 5502.6

C7 Naphthenes

Dimethylcyclopentanes C7H14 98.19 0.7592 5234.4 Methylcyclohexane

Methylcyclohexane C7H14 98.19 0.7744 5215.7

C7 Aromatics

Toluene C7H8 92.14 0.8852 4474.5 Toluene


72


Component Formula Molar Mass Relative Density

HHV Btu/scf

Surrogate

C8 Alkanes

2-Methylheptane C8H18 114.23 0.7027 6241.1

n-Octane 3-Methylheptane C8H18 114.23 0.7105 6244.4

n-Octane C8H18 114.23 0.7066 6249.0

C8 Naphthenes

Dimethylcyclohexanes C8H16 112.22 0.7856 5956.1 1,1-Dimethylcyclohexane

Trimethylcyclopentanes C8H16 112.22 0.7772 5985.1

C8 Aromatics

Ethyl benzene C8H10 106.17 0.8722 5221.7

Ethyl-benzene m-Xylene C8H10 106.17 0.8693 5207.4

p-Xylene C8H10 106.17 0.8661 5208.3

o-Xylene C8H10 106.17 0.8850 5209.4

Table B.11: C9 Alkanes and Naphthenes and Their Surrogates

Component Formula Molar Mass Relative Density

HHV Btu/scf

Surrogate

C9 Alkanes

C9 Paraffins C9H20 128.26 0.7151 6976.3 n-Nonane

n-Nonane C9H20 128.26 0.7222 6996.3

C9 Naphthenes

Trimethylcyclohexanes C9H18 126.24 0.7856 5964.2 1,1,2-

Trimethylcyclohexane

With these grouping and applied surrogates, the allocator arrives at the component list found in Table B.12. Each contributing liquid stream would have a unique C10+ pseudo-component derived from the MW and liquid density of each stream.


73

Table B.12: Component List Derived from Extended Analysis Component/Component Group Surrogate

Nitrogen Nitrogen

Carbon Dioxide Carbon Dioxide

Methane Methane

Ethane Ethane

Propane Propane

Iso-butane Iso-butane

n-Butane n-Butane

Iso-pentane Iso-pentane

n-Pentane n-Pentane

C6 Alkanes n-Hexane

C6 Naphthenes Cyclohexane

C6 Aromatics Benzene

C7 Alkanes n-Heptane

C7 Naphthenes Methylcyclohexane

C7 Aromatics Toluene

C8 Alkanes n-Octane

C8 Naphthenes 1,1-Dimethylcyclohexane

C8 Aromatics Ethyl benzene

C9 Alkanes n-Nonane

C9 Naphthenes 1,1,2-Trimethylcyclohexane

Decanes and heavier Pseudon (C10+)

As components get larger, the number of isomers, cyclics, aromatics, and other types of compounds increases. Analyses can easily get to over 150 components. The process described above can be carried further and into larger components. The allocator must find a balance between performance and practical application in selection of a component set.

Table B.13 and Table B.14 provide two example comparisons of results obtained using different component sets including 30 °API and 55 °API liquids.


74

Table B.13: Sample Comparison Using 30 °API Liquid

Component Lists:

C6+ C10+ Extended

Component Mol % Component Mol % Component Mol % Nitrogen 0.037 Nitrogen 0.037 Nitrogen 0.037

Methane 0.0221 Carbon dioxide 0.0221 Carbon dioxide 0.0221

Carbon dioxide 8.3772 Methane 8.3772 Methane 8.3772

Ethane 1.3211 Ethane 1.3211 Ethane 1.3211

Propane 3.2295 Propane 3.2295 Propane 3.2295

Isobutane 1.1791 Iso-butane 1.1791 Iso-butane 1.1791

n-Butane 3.7172 n-Butane 3.7172 n-Butane 3.7172

Isopentane 2.1348 Iso-pentane 2.1348 Iso-pentane 2.1348

n-Pentane 2.8335 n-Pentane 2.8335 n-Pentane 2.8335

Hexanes plus 77.1485 C6 Hexanes 3.5174 C6 Alkanes 2.1808

C7 Heptanes 5.0894 C6 Naphthenes 1.2663

C8 Octanes 5.3653 C6 Aromatics 0.0703

C9 Nonanes 3.2058 C7 Alkanes 1.8831

Decanes plus 59.9706 C7 Naphthenes 3.0027

C7 Aromatics 0.2036

C8 Alkanes 3.7385

C8 Naphthenes 0.661

C8 Aromatics 0.9658

C9 Alkanes 1.2182

C9 Naphthenes 1.9876

Decanes+ 59.9706

Conditions:

API gravity ° 30

Sample pressure, psig 300

Sample temperature, °F 90

Molecular weight 215

Density, lb/ft3 54.64

Results:

Property C6+ C10+ Extended

Bubble point pressure @temp 327.4 309.7 307.6

Shrunk density, lb/ft3 54.95 55 54.99

Shrinkage factor from pressure 0.9652 0.9626 0.9628

Shrinkage factor from bubble point 0.9643 0.9622 0.9625

Flash factor, MSCF/STB 71.3 72.5 72.6

Flash gas density, lb/ft3 0.0733 0.0756 0.0757

Flash gas GHV, Btu/scf 1633 1680.8 1681.6


75

Table B.14: Sample Comparison Using 55 °API Liquid

Component Lists:

C6+ C10+ Extended

Component Mol % Component Mol % Component Mol % Nitrogen 0.0758 Nitrogen 0.0758 Nitrogen 0.0758

Methane 0.0709 Carbon dioxide 0.0709 Carbon dioxide 0.0709

Carbon dioxide 33.48 Methane 33.48 Methane 33.48

Ethane 1.0962 Ethane 1.0962 Ethane 1.0962

Propane 1.2151 Propane 1.2151 Propane 1.2151

Isobutane 2.313 Iso-butane 2.313 Iso-butane 2.313

n-Butane 3.3215 n-Butane 3.3215 n-Butane 3.3215

Isopentane 1.3673 Iso-pentane 1.3673 Iso-pentane 1.3673

n-Pentane 2.1444 n-Pentane 2.1444 n-Pentane 2.1444

Hexanes plus 54.9158 C6 Hexanes 4.1325 C6 Alkanes 2.5027

C7 Heptanes 8.9674 C6 Naphthenes 1.5446

C8 Octanes 11.4933 C6 Aromatics 0.0852

C9 Nonanes 4.9794 C7 Alkanes 3.2918

Decanes plus 25.3433 C7 Naphthenes 5.249

C7 Aromatics 0.4265

C8 Alkanes 6.9195


C8 Aromatics 2.1666

C9 Alkanes 1.9165


Decanes+ 25.3433

Conditions:

API gravity ° 55

Sample pressure, psig 1250

Sample temperature, °F 70

Molecular weight 125

Density, lb/ft3 47.32

Results:

Property C6+ C10+ Extended

Bubble point pressure @temp 1319.5 1217.5 1176.9

Shrunk density, lb/ft3 49.94 49.93 49.85

Shrinkage factor from pressure 0.8846 0.8682 0.8686

Shrinkage factor from bubble point 0.8797 0.8678 0.8678

Flash factor, MSCF/STB 366.3 378.5 380

Flash gas density, lb/ft3 0.0592 0.0637 0.0644

Flash gas GHV, Btu/scf 1347.4 1438.9 1450.8


76

Annex C (informative)

EOS and EOS Tuning Examples The following examples are for illustration purposes only. They are not to be considered exclusive or exhaustive in nature. API makes no warranties, express or implied for reliance on or any omissions from the information contained in this document.

EXAMPLE 1 Basic Tuning Routine This is an example of a tuning tool that prepares a basic laboratory sample for use in an EOS process simulation model for allocation. Its only function is to match the EOS bubble point (saturation pressure) to the separator pressure at separation temperature. Establish Criteria The separator operates within a pressure range of 385 psig to 425 psig and a temperature range of 90 °F to 100 °F. the produced oil has a mole percent of methane of between 8% and 10%.

The laboratory composition will be defined by discrete and surrogate components and a single PsC. The C1-PsC binary interaction parameter (BIP) will be adjusted to reach the target saturation pressure (Psat).

The first step is to evaluate how this BIP impacts saturation pressure. A representative sample is obtained and defined using the established component set.

The component set, along with a mid-range temperature of 95 °F, are entered into the EOS model. The immediate goal here is to evaluate BIP impact not to hit a specific target. The resulting Psat is observed along with the model calculated BIP. The BIP is then set at an arbitrary low value (-0.05) and the Psat is recorded. They process is repeated several times, each time increasing the BIP value and recording the resulting Psat. This process continues until the resulting Psat well exceeds the allowable pressure range (0.2). The result is table of BIP and Psat values. See Table C. 1

Table C. 1: BIP impact on Psat BIP Psat, psig

-0.050 291.2 -0.025 309.8 0.000 329.9 0.025 351.7 0.050 375.3 0.075 400.9 0.100 428.7 0.125 458.9 0.150 491.8 0.175 527.7

0.200 566.9 These values are then plotted to observe graphically how BIP impacts Psat. See Figure C.1


77

Figure C.1: graphical illustration of the Psat BIP relationship.

By observation, the function, Psat = F(BIP), for this composition and BIP is near linear, so the tool will use the linear function y = A(x) + B to describe the relationship between the target parameter (y) to the fitting parameter (x), i.e. Psat to BIP. The relationship between the two parameters is not always linear. So long as they can be described mathematically, this process can be applied.

For the purposes of the application, the tool is good for liquids from this source, having a mole percentage of methane between 8 and 10, a temperature range of 90 °F to 100 °F, and a pressure range of 385 psig and 425 psig. The limitation on the BIPC1-PsC is -0.05 and 0.2.

Run Routine The tuning algorithm is an automated, iterative routine.

STEP1 The subject sample composition and separator temperature are entered into the tool. The EOS calculates BIPs for all component pairs. The output from the model is Psat.

STEP2 The BIPC1-PsC is set to the minimum (-0.05) and the Psat is recorded.

STEP3 The BIPC1-PsC is set to the maximum (0.2) and the Psat is recorded.

STEP4 Using the BIP and the resulting Psat, the A and B coefficients of the linear function are determined.

STEP5 Solving for the BIP using the target Psat, a first iteration BIP is calculated.

STEP6 The BIPC1-PsC is set to this value and the Psat is recorded.

STEP7 Because the function is not strictly linear, the resulting Psat will not equal the target Psat. See Figure C.1. To reach the target parameter, the minimum BIP is raised to the calculated BIP for a new iteration. This is because the resulting Psat had fallen short of the target. Had the target been overshot, the maximum BIP would have been lowered. Once the endpoints are adjusted, new A, B coefficients are calculated, and the routine iterates until a solution is found.

250.0

300.0

350.0

400.0

450.0

500.0

550.0

600.0

650.0

-0.050 0.000 0.050 0.100 0.150 0.200

psig

BIP

Psat vs BIP C1-PsC


78

Figure C.2: graphical illustration of the first iteration of the tuning process.

NOTE The minimum BIP is raised to the resulting BIP to zero in on the target. See Figure C.3.

Figure C.3 graphical illustration of the second iteration of the tuning process.


79

Table C. 2: Iterative results of the tuning process

Target = 420 psig Calculated

BIP Resulting

Psat Iteration Min BIP Max BIP Min Psat Max Psat A B

1 -0.050 0.2 317.6 600.4 1131.2 374.2 0.0405 395.1

2 0.041 0.2 395.1 600.4 1287.3 342.9 0.0599 414.7

3 0.060 0.2 414.7 600.4 1325.2 335.4 0.0639 418.9

4 0.064 0.2 418.9 600.4 1333.2 333.8 0.0647 419.8

5 0.065 0.2 419.8 600.4 1334.9 333.4 0.0649 420.0

This application is auditable and repeatable but very basic and likely to fit well over a broad range of conditions.

Most laboratory analyses used in allocation are basic single stage flash results and do not provide properties and compositions over a range of conditions. There are other target parameters to fit using BIP including the sample gas composition compared to equilibrium composition from the EOS tool. Here, all comp-PSC are adjusted while targeting both saturation pressure and equilibrium gas composition. Also, laboratory shrinkage factor can be targeted by adjusting the volume shift. Shrinkage factor and liquid density could be targeted together. Adjusting the BIP will have little effect on shrinkage, and volume shift will have little effect on saturation pressure.


80

Annex D (informative)

Validation and Acceptance Criteria Examples The following examples are for illustration purposes only. They are not to be considered exclusive or exhaustive in nature. API makes no warranties, express or implied for reliance on or any omissions from the information contained in this document.

The following list provides example uncertainty ranges for acceptance criteria that are used for compositional component validation between EOS-calculated values and laboratory-derived values. The ranges of uncertainties are applicable for a pressure range of 0 kPa to 11,700 kPa (0 psig to 1700 psig) and temperatures from –6 °C to 74 °C (20 °F to 165 °F).

— Volatile oil (758.7 kg/m3 to 815.6 kg/m3, 55 °API to 42 °API) bubble point/saturation pressure: ±5 %.

— Black oil (801.7 kg/m3 to 965.9 kg/m3, 45 °API to 15 °API) bubble point/saturation pressure: ±2 % to ±5 %.

— Hydrocarbon dew point/saturation temperature: ±10 %.

— GOR: ±10 %.

— Density: ±2 %.

— Bo/Bg: ±5 %.

— Gas compositions mole fraction: ±5 %.

— MW: ±10 %.


81

Annex E (informative)

Fluid Characterization Validation Examples The following examples are for illustration purposes only. They are not to be considered exclusive or exhaustive in nature. API makes no warranties, express or implied for reliance on or any omissions from the information contained in this document.

EXAMPLE 1 Adequacy of Tuning Methodology This is an example of a tuning methodology (fluid characterization). An automated process is used to tune sample data to determine shrink and flash factions for use in an allocation. The methodology is validated against PVT study data and other laboratory analysis.

Initially, the tuning was to be performed by simply adjusting the BIPC1-PsC to match saturation pressure and PsC volume translation to match shrink.

The model was tuned to laboratory provided shrink and flash determined by basic C7+ analyses. The separator gas stream was also analyzed to C6+. The results are shown in Table E.1.

Table E.1: initial tuning results Model Sample Saturation Pressure, psig 220 220 Shrink 0.8983 0.8983 Flash 131.8 143.4 Separator Gas Composition Nitrogen 3.6392 1.8157 CO2 0.1975 0.2005 Methane 75.1648 75.3366 Ethane 12.4053 12.8115 Propane 5.9914 6.6231 i-Butane 0.4751 0.5704 n-Butane 1.4926 1.6355 i-Pentane 0.2400 0.3023 n-Pentane 0.2903 0.3220 C6+ 0.1037 0.3824

The saturation pressure and shrink, the two target parameters, are a match. The flash, which was not a target parameter, does not match well. Note that the gas composition matches well for some but not all components.

The liquid and gas compositions were recombined at proportions equal to the proportions at the time of the sampling. The model was run with the combined stream composition and the resulting shrink and flash ware calculated over a range of pressures and temperatures and compared to the baseline data. See Table E.2 and Table E.3. See Figure E.1 for a graphical illustration of flash error.


82

Table E.2: initial tuning shrink error Pressure

Temperature 200 210 220 230 240 250 70 0.00% 0.04% 0.07% 0.11% 0.14% 0.17% 80 -0.04% 0.00% 0.04% 0.07% 0.10% 0.14% 90 -0.08% -0.04% 0.00% 0.03% 0.07% 0.10%

100 -0.11% -0.07% -0.04% 0.00% 0.03% 0.07% 110 -0.15% -0.11% -0.07% -0.04% 0.00% 0.03% 120 -0.18% -0.15% -0.11% -0.07% -0.04% -0.01%

Table E.3: initial tuning flash error Pressure

Temperature 200 210 220 230 240 250 70 -8.01% -7.96% -7.93% -7.89% -7.85% -7.82% 80 -8.07% -8.03% -7.99% -7.96% -7.92% -7.89% 90 -8.11% -8.07% -8.04% -8.00% -7.97% -7.94%

100 -8.12% -8.09% -8.06% -8.03% -8.00% -7.97% 110 -8.09% -8.07% -8.04% -8.02% -7.99% -7.97% 120 -8.03% -8.01% -7.99% -7.97% -7.96% -7.94%

Figure E.1: graphically depiction of initial tuning flash error


83

While the shrink showed little variation, the flash was off almost a constant 8%. It was thought that by matching shrink, flash would naturally fall in line. That was not the case.

To remedy the situation, another target parameter was needed. If volume translation were used, it would have to involve other components beyond the single PsC. Adjusting acentricity or critical properties would work against other fluid properties and likely require adjustment to other components. The desire was to limit the tuning to the PsC to accommodate the overall system design. To fit the flash factor, all PsC BIPs would be adjusted to better match the sample gas to the EOS gas composition while still hitting saturation pressure and shrink. The results of the improved methodology are shown in Table E.4.

Table E.4: improved tuning output Model Sample Saturation Pressure, psig 220 220 Shrink 0.8983 0.8983 Flash 143.4 143.4 Separator Gas Composition Nitrogen 1.7682 1.8157 CO2 0.1988 0.2005 Methane 75.9384 75.3366 Ethane 12.5155 12.8115 Propane 6.4335 6.6231 i-Butane 0.5589 0.5704 n-Butane 1.5934 1.6355 i-Pentane 0.2947 0.3023 n-Pentane 0.3202 0.3220 C6+ 0.3783 0.3824

Note that the flash has now fallen into place while maintaining saturation pressure and shrink. Combining the liquid and gas compositions again and processing them over a range of pressures and temperatures, the results showed a big improvement to flash with little to no impact on shrink. The adjustment of the BIPs had little on shrink. See Table E.5 and Table E.6. See Figure E.2 for a graphical depiction of the flash error.

Table E.5: improved tuning shrink error Pressure

Temperature 200 210 220 230 240 250 70 -0.01% -0.01% -0.01% -0.02% -0.02% -0.02% 80 0.01% 0.01% 0.01% 0.01% 0.01% 0.01% 90 0.03% 0.03% 0.03% 0.03% 0.03% 0.03%

100 0.06% 0.06% 0.06% 0.06% 0.05% 0.05% 110 0.08% 0.08% 0.08% 0.08% 0.08% 0.08% 120 0.10% 0.10% 0.10% 0.10% 0.10% 0.10%


84

Table E.6: improved tuning flash error Pressure

Temperature 200 210 220 230 240 250 70 0.68% 0.69% 0.71% 0.72% 0.74% 0.75% 80 0.53% 0.54% 0.56% 0.58% 0.60% 0.61% 90 0.38% 0.40% 0.42% 0.44% 0.45% 0.47%

100 0.23% 0.25% 0.27% 0.29% 0.31% 0.33% 110 0.08% 0.10% 0.13% 0.15% 0.17% 0.19% 120 -0.06% -0.03% -0.01% 0.01% 0.03% 0.05%

Figure E.2: graphical depiction of improved tuning flash error


85

Annex F (informative)

Input Data Validation The following examples are for illustration purposes only. They are not to be considered exclusive or exhaustive in nature. API makes no warranties, express or implied for reliance on or any omissions from the information contained in this document.

EXAMPLE 1 Data validation by comparing net theoretical production to sales on a daily basis

Table F.1 Below shows the result of applying a shrinkage to the separator measured oil volumes. The total (Separator Total) is compared to the measured sales oil for the day. The net difference is flagged. Gross imbalances are indication of suspect data and triggers an investigation.

Table F.1: Oil Balance DAY OF THE MONTH 1 2 3 4 5 6

OIL BALANCE SHRINK SEP A 0.9572 33,027 32,871 32,860 32,799 32,744 32,706

SEP B 0.9508 3,263 3,259 3,216 3,231 3,239 3,265

SEP C 0.9757 3,972 3,930 3,941 3,879 3,843 3,850

SEPD 0.7740 547 484 536 566 970 830

SEP E 0.8855 9,140 9,138 9,132 9,418 9,483 9,406

SEP F 0.9281 4,905 4,901 4,894 4,888 4,881 4,873

SEP G 0.9229 9,149 9,117 9,074 9,040 9,035 3,832

Separator Total 64,004 63,699 63,652 63,820 64,195 58,761

Sales Oil 68,659 64,445 64,217 64,217 71,637 52,562

Sales - Net Difference 4,655 746 565 397 7,442 -6,199

Balance 6.78% 1.16% 0.88% 0.62% 10.39% -11.79%

Table F.2 Below shows the result of adding the separator gas volume to a flash volume calculated by multiplying measured oil by a flash factor and adjusting for fuel, flare, and recirculation. The total (Separator Total) is compared to the measured sales oil for the day. The net difference is flagged. Gross imbalances are indication of suspect data and triggers an investigation.

Table F.3 below shows the result of a calculated ratio of gas to oil volumes. The ratio is typically consistent from day to day. Changes in ratio, coupled with imbalances are indication of measurement issues.


86

Table F.2: Gas Balance DAY OF THE MONTH 1 2 3 4 5 6 GAS BALANCE

SEP A 42,828 42,619 42,560 42,506 42,621 42,551

SEP B 16,753 16,743 16,730 16,716 16,646 16,596

SEP C 6,118 6,100 6,009 5,933 5,880 5,739

SEPD 12,380 12,155 12,124 12,143 17,808 27,764

SEP E 7,389 7,384 7,369 7,385 7,351 7,365

SEP F 6,038 6,022 5,983 5,969 5,891 5,866

SEP G 30,416 30,281 30,321 30,306 30,365 16,023 Flash Gas GOR

SEP A 62.68 2,070 2,060 2,060 2,056 2,052 2,050

SEP B 76.14 248 248 245 246 247 249

SEP C 57.44 228 226 226 223 221 221

SEPD 575.63 315 279 308 326 558 477

SEP E 71.62 655 654 654 674 679 674

SEP F 64.25 315 315 314 314 314 313

SEP G 87.80 803 800 797 794 793 336

Recirculation

SEP A 5,485 5,325 5,296 5,327 5,542 5,501

Fuel/Flare 7,269 7,125 7,001 7,027 7,989 6,879

Separator Total 121,921 121,303 121,096 120,957 126,561 121,905

Flash Total 4,635 4,583 4,604 4,633 4,864 4,320

Circulation Total 5,485 5,325 5,296 5,327 5,542 5,501

Fuel/Flare Total 7,269 7,125 7,001 7,027 7,989 6,879

Net Gas 113,802 113,436 113,403 113,236 117,894 113,845

Sales Gas 112,577 112,373 112,196 111,939 118,768 109,662

Sales - Net Difference -1,225 -1,063 -1,207 -1,297 874 -4,183

Balance -1.09% -0.95% -1.08% -1.16% 0.74% -3.81%

Table F.3: GOR GOR

SEP A 1.19 1.20 1.20 1.20 1.20 1.20

SEP B 5.21 5.21 5.28 5.25 5.21 5.16

SEP C 1.60 1.61 1.58 1.59 1.59 1.55

SEPD 23.21 25.67 23.20 22.01 18.94 34.05

SEP E 0.88 0.88 0.88 0.86 0.85 0.85

SEP F 1.30 1.29 1.29 1.29 1.27 1.27

SEP G 3.41 3.41 3.43 3.44 3.45 4.27


87

Annex G (informative)

Output Result Determination Examples The following examples are for illustration purposes only. They are not to be considered exclusive or exhaustive in nature. API makes no warranties, express or implied for reliance on or any omissions from the information contained in this document.

EXAMPLE 1- Approach to Shrinkage Factor Determination as a Function of Pressure and Temperature

This is a methodology development of a pressure and temperature based shrinkage factor that can be applied to measured oil production streams within an allocation process. The methodology includes a single formula with well specific coefficients for temperature and pressure variables. There is no current specific compositional data yet available for the wells in question. Data used for this preliminary development are from the Permian Basin area. Once the specific data is available the methodology will be adjusted to fit that data. The purpose of this paper is to communicate the intended approach.

The initial 10 compositional data sets will include liquid and gas compositions along with some fluid physical properties determined by laboratory analysis. These oil and gas streams will be recombined and tuned to match laboratory physical properties to make up full well streams. Each well will be assigned a full well stream composition from the initial 10 sets. Each well will also be assigned configuration from a group of five wellhead configurations. The shrinkage factor determination methodology will be applied to each well.

The shrinkage methodology determines a factor for a combination of pressures and temperatures ranging from 70°F to 130°F in increments of 10° and from 100 psig to 300 psig in increments of 10 psi, for a total of 147 data points. The temperature and pressure ranges can be adjusted once actual data is received. Table G.1 shows some results using preliminary data.


88

Table G.1: Preliminary shrink data for temperatures from 70 to 130°F and pressures from 100 to 300 psig

70 80 90 100 110 120 130 100 0.9596 0.9640 0.9673 0.9697 0.9712 0.9720 0.9723 110 0.9529 0.9579 0.9618 0.9646 0.9666 0.9678 0.9685 120 0.9462 0.9518 0.9562 0.9596 0.9620 0.9636 0.9646 130 0.9397 0.9458 0.9507 0.9545 0.9574 0.9594 0.9607 140 0.9332 0.9398 0.9452 0.9495 0.9527 0.9551 0.9568 150 0.9269 0.9340 0.9398 0.9445 0.9481 0.9509 0.9529 160 0.9207 0.9282 0.9344 0.9395 0.9435 0.9466 0.9489 170 0.9146 0.9225 0.9291 0.9346 0.9390 0.9424 0.9450 180 0.9086 0.9169 0.9238 0.9297 0.9344 0.9382 0.9411 190 0.9028 0.9113 0.9187 0.9248 0.9299 0.9340 0.9372 200 0.8971 0.9059 0.9136 0.9200 0.9254 0.9298 0.9333 210 0.8915 0.9006 0.9085 0.9153 0.9210 0.9256 0.9294 220 0.8860 0.8954 0.9036 0.9106 0.9166 0.9215 0.9255 230 0.8806 0.8902 0.8987 0.9060 0.9122 0.9174 0.9217 240 0.8753 0.8852 0.8939 0.9014 0.9079 0.9134 0.9179 250 0.8702 0.8802 0.8891 0.8969 0.9037 0.9094 0.9141 260 0.8651 0.8753 0.8845 0.8925 0.8994 0.9054 0.9103 270 0.8601 0.8705 0.8799 0.8881 0.8953 0.9014 0.9066 280 0.8552 0.8658 0.8753 0.8838 0.8912 0.8975 0.9029 290 0.8505 0.8612 0.8709 0.8795 0.8871 0.8936 0.8992 300 0.8458 0.8567 0.8665 0.8753 0.8831 0.8898 0.8956

The linearity of this data relative to pressure was checked and found to be within an acceptable range. If the data can be assumed linear, the overall shrinkage formula can be simplified. The results are shown in Table G.2.

Table G.2: relative linearity of shrinkage values as a function of pressure Temperature 70 80 90 100 110 120 130 R-squared 0.9971 0.9980 0.9987 0.9992 0.9995 0.9998 0.9999

R-squared is an indicator of how far off actual data points are from a trendline of the function. In this example, the trendline is a straight line. Note that the linearity improves with increasing temperature. Figure G.1 illustrates the SF function relative to pressure for the various temperatures.


89

Figure G.1: shrinkage vs pressure for various temperatures Given that at the lowest temperature the function is still to a large degree linear, it is assumed that shrinkage is linear relative to pressure and the equation for shrinkage as a function of pressure becomes:

𝑆𝑆𝑆𝑆 = 𝑀𝑀(𝑷𝑷) + 𝐼𝐼 Eqn. 1 Where:

SF = Shrinkage Factor

P = Pressure in psig

M = the slope of the SF function line

I= the intercept of the SF function line

Equation 1 will have unique M and I coefficients for a given temperature. Table G.3 shows the slope (M) and intercept(I) for each temperature evaluated.

Table G.3: Slope and intercept per temperature

M I Temperature Slope Intercept

70 -0.0006 1.0129 80 -0.0005 1.0151 90 -0.0005 1.0159

100 -0.0005 1.0157 110 -0.0004 1.0146 120 -0.0004 1.0128 130 -0.0004 1.0107

0.84000.85000.86000.87000.88000.89000.90000.91000.92000.93000.94000.95000.96000.97000.9800

100 120 140 160 180 200 220 240 260 280 300

Shrin

kage

Pressure

Shrinkage vs pressure @various temperatures

70

80

90

100

110

120

130


90

Figure G.2 shows that while the slopes of the pressure function relative to temperature is linear, the intercept of the pressure function is not.

Figure G.2: temperature vs pressure coefficients The slope of the pressure function (M) as a function of temperature can be represented by the equation:

𝑀𝑀 = 𝐶𝐶(𝑻𝑻) + 𝐷𝐷 Eqn. 2

Where:

M = slope of the pressure function

T = Temperature in °F

C = the slope of the pressure function line slope

D = the intercept of the pressure function line slope

The intercept of the pressure function (I) as a function of temperature can be represented by the equation:

𝐼𝐼 = 𝐴𝐴(𝑻𝑻2) + 𝐵𝐵(𝑻𝑻) + 𝐸𝐸 Eqn. 3 Where:

I = intercept coefficient of the pressure function

T = Temperature in °F

A = Second order coefficient of the pressure function line intercept

B = First order coefficient of the pressure function line intercept

C = constant of the pressure function line intercept

Combining Equations 1, 2, and 3

1.0100

1.0110

1.0120

1.0130

1.0140

1.0150

1.0160

1.0170

-0.0006

-0.0005

-0.0004

-0.0003

-0.0002

-0.0001

0.0000

60 70 80 90 100 110 120 130 140

Inte

rcep

t, I

Slop

e, M

Temperature

temperature vs pressure coefficients

Slope Intercept Linear (Slope) Poly. (Intercept)


91

𝑆𝑆𝑆𝑆 = 𝑀𝑀(𝑃𝑃) + 𝐼𝐼 Eqn. 1

𝑀𝑀 = 𝐶𝐶(𝑇𝑇) + 𝐷𝐷 Eqn. 2

𝐼𝐼 = 𝐴𝐴(𝑇𝑇2) + 𝐵𝐵(𝑇𝑇) + 𝐸𝐸 Eqn. 3

Yields:

𝑆𝑆𝑆𝑆 = [𝐶𝐶(𝑇𝑇) + 𝐷𝐷][𝑃𝑃] + [𝐴𝐴(𝑇𝑇2) + 𝐵𝐵(𝑇𝑇) + 𝐸𝐸] 𝑆𝑆𝑆𝑆 = 𝐴𝐴(𝑇𝑇2) + 𝐵𝐵(𝑇𝑇) + 𝐶𝐶(𝑇𝑇)(𝑃𝑃) + 𝐷𝐷(𝑃𝑃) + 𝐸𝐸 Eqn. 4

Each well will have a set of five coefficients (A, B, C, D, and E) for the determination of shrink factor from oil stream pressure and temperature applied in the following algorithm:

𝑺𝑺𝑭𝑭 = 𝑨𝑨(𝑻𝑻𝟐𝟐) + 𝑩𝑩(𝑻𝑻) + 𝑪𝑪(𝑻𝑻)(𝑷𝑷) + 𝑫𝑫(𝑷𝑷) + 𝑬𝑬

Applying the algorithm to the data collected in Table G.1 yields the applied algorithm results in Table G. 4 with the percent error in Table G.5.

Table G. 4: Applied Algorithm Results 70 80 90 100 110 120 130

100 0.9564 0.9612 0.9651 0.9682 0.9704 0.9717 0.9721 110 0.9507 0.9558 0.9600 0.9634 0.9659 0.9676 0.9683 120 0.9450 0.9504 0.9550 0.9587 0.9615 0.9634 0.9645 130 0.9393 0.9451 0.9499 0.9539 0.9570 0.9593 0.9606 140 0.9337 0.9397 0.9449 0.9492 0.9526 0.9551 0.9568 150 0.9280 0.9343 0.9398 0.9444 0.9481 0.9510 0.9530 160 0.9223 0.9290 0.9348 0.9397 0.9437 0.9469 0.9492 170 0.9166 0.9236 0.9297 0.9349 0.9393 0.9427 0.9453 180 0.9110 0.9182 0.9246 0.9302 0.9348 0.9386 0.9415 190 0.9053 0.9129 0.9196 0.9254 0.9304 0.9345 0.9377 200 0.8996 0.9075 0.9145 0.9207 0.9259 0.9303 0.9338 210 0.8939 0.9021 0.9095 0.9159 0.9215 0.9262 0.9300 220 0.8883 0.8968 0.9044 0.9112 0.9170 0.9220 0.9262 230 0.8826 0.8914 0.8993 0.9064 0.9126 0.9179 0.9224 240 0.8769 0.8860 0.8943 0.9017 0.9082 0.9138 0.9185 250 0.8713 0.8807 0.8892 0.8969 0.9037 0.9096 0.9147 260 0.8656 0.8753 0.8842 0.8922 0.8993 0.9055 0.9109 270 0.8599 0.8699 0.8791 0.8874 0.8948 0.9014 0.9070 280 0.8542 0.8646 0.8741 0.8826 0.8904 0.8972 0.9032 290 0.8486 0.8592 0.8690 0.8779 0.8859 0.8931 0.8994 300 0.8429 0.8539 0.8639 0.8731 0.8815 0.8890 0.8955


92

Table G.5: Percentage error incurred with algorithm

70 80 90 100 110 120 130 100 -0.3% -0.3% -0.2% -0.2% -0.1% 0.0% 0.0% 110 -0.2% -0.2% -0.2% -0.1% -0.1% 0.0% 0.0% 120 -0.1% -0.1% -0.1% -0.1% -0.1% 0.0% 0.0% 130 0.0% -0.1% -0.1% -0.1% 0.0% 0.0% 0.0% 140 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 150 0.1% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 160 0.2% 0.1% 0.0% 0.0% 0.0% 0.0% 0.0% 170 0.2% 0.1% 0.1% 0.0% 0.0% 0.0% 0.0% 180 0.3% 0.2% 0.1% 0.1% 0.0% 0.0% 0.0% 190 0.3% 0.2% 0.1% 0.1% 0.1% 0.1% 0.1% 200 0.3% 0.2% 0.1% 0.1% 0.1% 0.1% 0.1% 210 0.3% 0.2% 0.1% 0.1% 0.1% 0.1% 0.1% 220 0.3% 0.2% 0.1% 0.1% 0.1% 0.1% 0.1% 230 0.2% 0.1% 0.1% 0.0% 0.0% 0.1% 0.1% 240 0.2% 0.1% 0.0% 0.0% 0.0% 0.0% 0.1% 250 0.1% 0.1% 0.0% 0.0% 0.0% 0.0% 0.1% 260 0.1% 0.0% 0.0% 0.0% 0.0% 0.0% 0.1% 270 0.0% -0.1% -0.1% -0.1% -0.1% 0.0% 0.0% 280 -0.1% -0.1% -0.1% -0.1% -0.1% 0.0% 0.0% 290 -0.2% -0.2% -0.2% -0.2% -0.1% -0.1% 0.0% 300 -0.3% -0.3% -0.3% -0.2% -0.2% -0.1% 0.0%


93

Annex H (informative)

Output Result Validation Examples The following examples are for illustration purposes only. They are not to be considered exclusive or exhaustive in nature. API makes no warranties, express or implied for reliance on or any omissions from the information contained in this document.

EXAMPLE 1. Overall Material and Energy Balance Validation Example

One method used to validate PSM output includes comparing theoretical values calculated by the PSM to actual sales data. Another method is to track relationships between certain key PSM inputs and outputs. The acceptance criteria used in these methods can also be categorized two ways. The first is an established range the parameter must fall within. The second is an allowable deviation of a parameter from a set of historical values.

Tables H.1, Table H.2, and Table H.3 provide an example of an allocation validation process incorporating the two validation methods described and using the two types of acceptance criteria.

Table H.4: Sales and Consumption LACT, bbl 2,040,000

Sales gas volume, MSCF 4,632,000

Sales gas energy, MMBtu 5,484,288

Sales gas energy content, Btu/SCF 1184.00

Fuel/flare volume, MSCF 178,000

LACT The net oil volume as received by the pipeline. It is the basis for payment and the volume that is ultimately allocated to the sources.

Sales Gas Volume The net gas volume as received by the pipeline. It is the volume that is ultimately allocated to the sources.

Sales Gas Energy The net gas energy as received by the pipeline. It is the basis for payment and ultimately allocated to the sources. This value is a product of the Sales Gas Volume and Sales Gas Energy Content.

Sales Gas Energy Content Gross heat value of the sales gas. It is a function of the composition of the sales gas.

Fuel/Flare Volume The volumes associated with fuel and flare. They can be measured, calculated, or estimated. The energy content of these streams can be a function of the actual source stream or an estimated value using a stream with a known energy content such as Sales Gas Energy Content.


94

Table H.5: Model inputs/outputs Separator

Measured Oil Volume

Separator Measured Gas Volume

Calculated Flash Gas

Volume

Separator Energy Content

Sales Theoretical Oil Volume

Sales Theoretical Gas Volume

Sales Theoretical Gas Energy

bbl MSCF MSCF Btu/SCF bbl MSCF MMBtu

Separator 1 200,628 1,500,000 96,415 1218.78 167,867 1,585,631 1,932,530

Separator 2 408,828 1,000,000 151,362 1192.89 356,312 1,123,149 1,339,790

Separator 3 612,350 720,000 120,083 1184.71 565,135 811,066 960,876

Separator 4 1,020,787 800,000 128,918 1152.58 966,432 882,064 1,016,651

Total 2,242,593 4,020,000 496,778 1192.63 2,055,746 4,401,910 5,249,847

Separator Measured Oil Volume Actual liquid volume totalized at the separator meter, less water, over the allocation period. This is typically stated at actual conditions (not standard).

Separator Measured Gas Volume Gas volume totalized at the separator meter over the allocation period. This is typically stated at standard conditions.

Calculated Flash Gas Volume Gas that evolves from the processing liquid. It is calculated by the PSM.

Separator Energy Content Gross Heat Value of the gas, both primary and flash, associated with a separator. It is a function of the Sales Theoretical Gas Volume and the Sales Theoretical Gas Energy of a separator.

Sales Theoretical Oil Volume The theoretical oil volume contribution of a separator at the sales point, calculated in the allocation scheme using PSM outputs.

Sales Theoretical Gas Volume The theoretical gas volume contribution of a separator at the sales point, calculated in the allocation scheme using PSM outputs. It represents both primary and flash gas volume.

Sales Theoretical Gas Energy The theoretical gas energy contribution of a separator at the sales point, calculated in the allocation scheme using PSM outputs. It represents both primary and flash gas energy. It is a function of the Sales Theoretical Gas Volume and its composition.


95

Table H.6: Validation parameters

Separator GOR

Separator Shrinkage

Factor

Separator Flash Factor

Separator Primary Gas

Factor

Oil

Balance

Gas Volume Balance

Gas Energy Balance

Separator 1 7.48 0.8367 574.36 0.9928

Separator 2 2.45 0.8715 424.80 0.9718

Separator 3 1.18 0.9229 212.49 0.9597

Separator 4 0.78 0.9468 133.40 0.9414

Total 1.79 0.9167 241.65 0.9714 –0.0077 0.0112 0.004

Separator GOR- The ratio of the Measured Gas Volume to the Measured Oil Volume.

It is not impacted by the PSM. For a steady-state operation, this GOR would remain fairly constant with change occurring with changing separator operating conditions or change in well alignment. Anomalies usually indicate a meter or water cut problem. The acceptance criteria would be a function of tracked historical data and documented change.

Separator Shrink Factor-The ratio of Sales Theoretical Oil Volume to the Measured Oil Volume.

It captures the volume change due to flashing, commingling with other liquids, condensate return from compression, and volume changes due to pressure and temperature adjustments to bring the fluid to standard conditions. This is not equivalent to a laboratory measured shrink. For a steady-state operation, this Shrink Factor would remain fairly constant with change occurring with changing separator operating conditions or change in well alignment. However, changes elsewhere in the process can impact this value. Anomalies could indicate compositional or process data, i.e. pressure and temperature problems. Anomalies could also be caused by problems with the PSM. The acceptance criteria would be a function of tracked historical data and documented change.

Separator Flash Factor- The ratio of Calculated Flash Gas Volume to the Sales Theoretical Oil Volume.

For a steady-state operation, this Flash Factor would be expected to remain fairly constant with change occurring with changing separator operating conditions or change in well alignment. However, changes elsewhere in the process can impact this value. Anomalies could indicate compositional or process data, problems. Anomalies could also be caused by problems with the PSM. The acceptance criteria would be a function of tracked historical data and documented change.

Separator Primary Gas Factor-The ratio of Sales Theoretical Gas Volume less Calculated Flash Gas Volume to Measured Separator Gas Volume for each separator.

This is a comparison of a calculated primary gas to measured one. The ideal value is 1.000. Anomalies could indicate compositional or process data, problems. Anomalies could also be caused by problems with the PSM. Although called a primary gas factor, the typical cause of a problem usually lies with the calculation of flash gas. The acceptance criteria would be a function of an established acceptable range of values.

Oil Balance-The ratio of the difference between the LACT and the Total Sales Theoretical Oil Volume to the LACT.

Anomalies here typically occur due to mismeasurement. This mismeasurement can occur directly at the separator meter or indirectly at a recirculation meter. Water cut can also be a factor. Gross compositional errors, either oil or gas can cause a large imbalance. A PSM that consistently mis-predicts bubble point or dew point can also contribute. There often are multiple contributors to an imbalance. The acceptance criteria would be a function of an established acceptable range of values. Systems with a well-designed and


96

maintained measurement system could run as tight as a +1 % to –2 % range.

Gas Volume Balance-The ratio of the difference between the Sales Gas Volume and the Total Theoretical Sales Gas Volume to the Sales Gas Volume. Anomalies here typically occur due to mismeasurement.

This mismeasurement can occur directly at the separator meter or indirectly at a recirculation meter. The acceptance criteria would typically be a function of an established acceptable range of values. Systems with a well-designed and maintained measurement system could run as tight as a +1 % to –2 % range.

Gas Energy Balance-The ratio of the difference between the Sales Gas Energy and the Total Theoretical Sales Gas Energy to the Sales Gas Energy.

Anomalies here, when they occur in conjunction with anomalies with the Gas Volume Balance, typically occur due to mismeasurement. This mismeasurement can occur directly at the separator meter or indirectly at a recirculation meter. The acceptance criteria would be an established acceptable range of values. Systems with a well-designed and maintained measurement system could run as tight as a +1 % to –2 % range. When there is a large difference between the Gas Volume Balance and the Gas Energy Balance, one cause could be that the system has had a large change in gas production. This change is captured with representative measurement and sampling, but the gas pipeline gas sample does not reflect the change. This results in consistent volume but inconsistent energy. Another cause could be that the PSM is wrongly predicting flash gas compositions or gas samples are not validated. In any event, the difference between the two factors can, in itself, be an acceptance criterion. If the pipeline is deemed not the problem, then an internal validation procedure can be implemented.

In general, these balance factors will catch measurement and instrumentation issues. If compositional data are properly validated, problems in the PSM will typically be too subtle to be caught in the oil and gas balances. Although a PSM impact can be substantial, it will be smaller than the acceptable range of uncertainty in a typical measurement system. Other Balance criteria such as oil density can be implemented to more closely monitor the PSM. Internal Balance Validations are better suited for catching PSM problems.


97

Bibliography

[1] API MPMS Chapter 8.1, Standard Practice for Manual Sampling of Petroleum and Petroleum Products

[2] API MPMS Chapter 8.2, Standard Practice for Automatic Sampling of Liquid Petroleum and Petroleum Products

[3] API MPMS Chapter 11.1, Temperature and Pressure Volume Correction Factors for Generalized Crude Oils,

[4] Refined Products, and Lubricating Oils

[5] API MPMS Chapter 12.3, Volumetric Shrinkage Resulting From Blending Light Hydrocarbons with Crude Oils

[6] API MPMS Chapter 14.1, Collecting and Handling of Natural Gas Samples for Custody Transfer

[7] API MPMS Chapter 14.5, Calculation of Gross Heating Value, Relative Density, Compressibility and Theoretical Hydrocarbon Liquid Content for Natural Gas Mixtures for Custody Transfer (GPA 2172)

[8] ASTM D2503, Standard Test Method for Relative Molecular Mass of Hydrocarbons by Thermoelectric Measurement of Vapor Pressure

[9] ASTM D4052, Standard Test Method for Density, Relative Density and API Gravity of Liquids by Digital Density Meter

[10] ASTM D5002, Standard Test Method for Density, Relative Density and API Gravity of Liquids by Digital Density Analyzer

[11] EI HM 96, Guidelines for the Allocation of Fluid Streams in Oil and Gas Production

[12] GPA 2172, Calculation of Gross Heating Value, Relative Density, Compressibility and Theoretical Hydrocarbon Liquid Content for Natural Gas Mixtures for Custody Transfer (API MPMS Chapter 14.5)

[13] GPA 2186, Method for the Extended Analysis of Hydrocarbon Liquid Mixtures Containing Nitrogen and Carbon Dioxide by Temperature Programmed Gas Chromatography

[14] GPA 2261, Analysis for Natural Gas and Similar Gaseous Mixtures by Gas Chromatography

[15] GPA 2286, Tentative Method of Extended Analysis for Natural Gas and Similar Gaseous Mixtures by Temperature Programmed Gas Chromatography

manual of petroleum measurement standards chapter...

Documents