static model development

- Kunal RathodFinal year petroleum engineering student of

School of Petroleum Technology, RaisanYear : 2012-13

Static Model Development

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Static model development |

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This presentation is a part of our B.Tech project “A comprehensive

study of effect of well spacing on ultimate recovery”.

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Introduction to static reservoir modeling

For decision making and improving the estimation of reserves; a computer model of a reservoir is constructed which we call as “The Reservoir Model”.

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Real Model Computer Model ……How ??

CLICK HERE FOR MORE INFO

Building the model

So this is how it may be done…!!?


Geocellular modelingIt is a way to describe the subsurface in 3D space (mathematically), which is constrained by a structural and stratigraphic framework.In a layman’s language, it is the process of generating the model/prototype of the subsurface. This model will resemble the real reservoir model. The physical properties of the reservoir are stored at the grid points or at the centers of gravity (3D voxels).

So the first thing is to define the GRID

Grid The simulation grid is the definition of how we divide, or discretize, space in order to solve the differential equations numerically. Common grid co-ordinate system includes Cartesian Cylindrical Corner Point Curvilinear


Grid Simulation |

Selection of proper GRIDIt is necessary that the grid that is defined should have desired level of accuracy in the solution of the flow equations; properly represents the reservoir geology; locations of wells, boundaries, faults, etc. and has the lowest computer memory and time requirements to solve the problem.

Common rules of constructing GRID In case of cylindrical grid system, the grid spacing is at logarithmic scale difference. The grid spacing should be such that the adjacent block size should not increase by the factor more that 3. Even the pressure drop between the blocks should not decrease by 30-20 %. Reservoir flow units should be separated by grid block boundaries. Vertical discretization should be fine enough for accurate accounting of gas percolation and migration and/or gravity over-ride or under-ride

Grid Simulation | using CMG simulator (version 2007.1)

GRID type (Cartesian, corner or cylindrical)

# of grid blocks in x, y and z direction respectively

Here, 10 is width of the block and 3 is the # of blocks in

each direction

Grid Simulation | using CMG simulator (version 2007.1)

A block with width 10m each

in x, y & z direction

Date @ which simulation starts

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Once the GRID is defined properly all we need to do is to give “LIFE” to our model …

Which can be done in 4 stages :

Structural Modeling

Stratigraphic Modeling

Lithological Modeling

Petrophysical Modeling

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Identifying the Structural top &

Interpreting the set of faults

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Structural modeling

Identifying structural topStructural top identification means recognizing the geometric structure of hydrocarbon trap. The workflow(in petrel) for the same would be :

Load SEG-Y format data.

Interpret it manually.

Full range of tools allows us to take a traditional line-by-line approach combined with the latest algorithms and tools including amplitude & waveform based tracking for best interpretation, allowing us to achieve rapid results

Structural Modeling |Using Petrel 2009 Seismic Simulator

Interpreting set of faultsSince the presence of fault/set of faults directly makes a huge difference to the field development plan and production characteristics…we need to carefully investigate it’s presence.Fault can be interpreted in the same way (as we seen the workflow in case of structural top).

But consider only Sealing faults !!!

BUT STILL …THERE CAN BE NUMEROUS FAULTS

SO, MANUAL INTERPRETATION BECOMES TEDIOUS !



So many faults

Can we do it automatically ?

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The Petrel Automated Structural Interpretation module uses an advanced computing algorithm "AntTracking" to overcome the tedious task.

Benefits :

Increases structural accuracy and detail & thus provides unbiased, repeatable & highly detailed mapping of discontinuities.

Significantly reduces tedious manual interpretation time.

All u need is ANT TRACKING module

The Ant Tracking workflow consists of four independent steps:


Step 1

Enhance the spatial discontinuities in your seismic data using any edge detection algorithm (i.e. variance, chaos, edge detection) and optionally, pre-condition your seismic data by reducing noise.

Step 2 Generate the Ant Track Cube and extract the fault patches.

Step 3 Validate and edit the fault patches.

Step 4 Create final fault interpretation model.

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Well-to-Well correlation :

The basic data used for well-to-well correlations are the

logs recorded in open hole or cased hole, and cores.

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Stratigraphic modeling

Analytically the best technique to establish the correlation between the geological units is by using the sequence stratigraphic method.

As per this technique the deposition of sedimentary bodies is governed by the combined effects of changes in sea-level, sedimentation, subsidence and tectonics.

On this basis, we can identify sequences of different hierarchical order within a geological unit that are separated by sequence boundaries which represent Unconformities or maximum flooding surfaces.

Stratigraphic Modeling |Analytical approach


Biostratigraphy

Production data (density, GOR etc.)


Drilling Data (ROP)

Formation & Pore pressure

In Petrel we can display and organize your logs in a flexible 2D visualization environment.

Stratigraphic Modeling |Petrel v2009 Simulator

A flexible 2D canvas allows simultaneous display of logs, seismic, 3D grid, and simulation results.

Stratigraphic Modeling |Petrel v2009 Simulator

Stratigraphic Modeling | Petrel v2009 Simulator

The workflow for correlation can be given as follows :

[1] Import well log las-file data :By importing well trajectories, well deviations and logs(las file) you can pick/select any horizon top and analysis it.

[2] Create cross sections :Under “window” option select “new well section window”. Then you can select the #of wells (to display their cross section)

Then after you can carry out other secondary operations (colorfill, thickness etc.)


[3] Revise formation top picks & compare: Pick horizon tops in the well panel and see the effects directly in 3D, or vice versa.Now you can compare the required section of the well log to other sections by using “ghost curve” option in the right hand side bar of petrel.Using ghost curve you can clip out a small section of your seismic and drag it over to other parts to correlate acrossfaults. (refer to next slide)


Now after selecting the portion, you can drag it to the other portion of the log to figure out the similarity between them.(see the yellow curves in box)This operation is called ghosting.

[4] Evaluate real-time updated picks in 2D and 3D interpretation windows :You can view the real time updated picks by turning ON (simply click on it) the well section fence.

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Identifying and recovering hydrocarbons requires an

accurate, high-resolution geological model of the reservoir

structure and stratigraphy.

Sedimentological Model Classification of facies

3D distribution of facies

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Lithological modeling

As a rule, facies Modeling can be performed using appropriate deterministic or stochastic functions which allow us to generate 2 or 3 dimensional spatial distributions of significant characteristics, such as porosity and permeability, directly from well data.

The idea behind this procedure is that the petrophysical characteristics of the reservoir can be considered intimately linked to the lithological facies.

In practical terms, the lithological model of a reservoir is constructed by integrating an ideal representation of the reservoir (sedimentological model), a classification stage (definition of facies) and a spatial distribution stage (three-dimensional model).

Lithological Modeling |

Lithological Modeling

3D distribution of facies

Sedimentological Model

Classification of facies


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.Example of a stochastic model of

facies

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Deterministic Model

Stochastic Model

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Petrophysical modeling

The values between the cells are interpolated by various techniques. Two of the important techniques are:

• Deterministic Model• Stochastic Model

Deterministic Model

It uses moving average method, based on inverse distance weighting.• Open the petrophysical process option from the menu.(this will open a dialog box)• From the dialog box, select Use Existing Property and select the Porosity property as the property to be modeled from the drop down menu.

Petrophysical Modeling |using Petrel v2004

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.• Select the Moving average as the Method; leave all other settings as default.• Click on OK; display the model in 3D window and it would appear like :

Stochastic ModelThis method uses Sequential Gaussian Simulation method. To create stochastic Modeling follow the given steps:

• Open the Petrophysical Modeling process. Go to the Use Existing property and select Porosity from the drop-down list.• Activate the required zone by clicking on the zone tab.• Select Sequential Gaussian Simulation as the method to use.• In variogram tab, select the Variogram type. In it select the Major Range, Minor Range, Vertical Range and Azimuth. Then after click on OK and create the property model.

Petrophysical Modeling |using Petrel v2004

. .Stochastic method : user defined variogram and range.

Journal article, organization as author :ESSCA Group, L'ESSCA, la Grande Ecole directement Petrel 2009 Seismic to Simulation Software, 2009.Petrel-A Schlumberger product group, Release notes; Petrel™ Workflow Tools 2004, November 2004.

Encyclopaedia on the Internet : Portale Treccani. L'enciclopedia Italiana; Oil Field Characteristics and Relevant Studies [Internet] , Italy Inc.; 2008, Available from : http://www.treccani.it/enciclopedia/oil-field-characteristics-and-relevant-studies_(altro)/

Part of an Internet website :West Virginia University, Department of Geology and Geography [Homepage on Internet], West Virginia : The University; c2008, Available from : http://www.geo.wvu.edu/~wilson/casi/

References |

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http://www.treccani.it/enciclopedia/oil-field-characteristics-and-relevant-studies_(altro)/

static model development

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