01. historical-based probability estimation for onshore pipelines

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Table of ContentsA. HISTORICAL-BASED PROBABILITY ESTIMATION FOR ONSHORE

PIPELINES.............................................................................................................. A.1

A.1 Scope ...........................................................................................................A.1

A.2 Approach ......................................................................................................A.1A.3 Baseline Failure Rates .................................................................................A.2A.4 Failure Mode Factor .....................................................................................A.3A.5 Failure Rate Models and Attribute Modification Factors...............................A.4

A.5.1 External Corrosion ............................................................................A.4A.5.2 Internal Corrosion .............................................................................A.9

A.5.2.1 Overview...........................................................................A.9A.5.2.2 Simplified Model ...............................................................A.9A.5.2.3 Refined Model ................................................................A.12

A.5.2.3.1 Liquid Product Corrosion ................................A.12A.5.2.3.2 Wet Gas Corrosion .........................................A.16

A.5.3 Equipment Impact...........................................................................A.20

A.5.3.1 Overview.........................................................................A.20A.5.3.2 Rate of Occurrence of Equipment Impact ......................A.22A.5.3.3 Probability of Failure Given Impact.................................A.23A.5.3.4 Model Scale Factor.........................................................A.25

A.5.4 Geotechnical Hazards ....................................................................A.26A.5.5 Stress Corrosion Cracking..............................................................A.28A.5.6 Manufacturing Cracks.....................................................................A.33A.5.7 Seismic Hazards.............................................................................A.35

A.5.7.1 Overview.........................................................................A.35A.5.7.2 Failure Rate due to Lateral Spreading of Liquefied

Soil..................................................................................A.37A.5.7.3 Guidance on Characterizing Soil Liquefaction

Susceptibility...................................................................A.41A.5.8 Other Causes..................................................................................A.42A.5.8.1 Overview.........................................................................A.42A.5.8.2 Gas Pipelines .................................................................A.43A.5.8.3 Liquid Pipelines ..............................................................A.43

A.6 Effective Age ..............................................................................................A.43A.7 References .................................................................................................A.46

March 2003 PIRAMID Technical Reference Manual


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A.1

A. Historical-Based Probability Estimation forOnshore Pipelines

A.1 ScopeThis document describes a set of historical-based models developed to calculate the rates of

failure by small leak, large leak or rupture for a given section of an onshore pipeline. The

models are based on historical incident data and algorithms that depend on specific line

attributes. The historical-based models were developed with an emphasis on simplicity,

efficiency and minimal data requirements based on a combination of statistical analysis,

simplified models and, where necessary, engineering judgment. The failure causes addressed

by the historical-based models are: external metal loss, internal metal loss corrosion,

equipment impact, geotechnical hazards, stress corrosion cracking, manufacturing cracks

(seam weld fatigue), seismic hazards, and other (or miscellaneous) causes.

A.2 Approach

For a majority of the failure causes considered, the annual rate of failure for a section of

pipeline is calculated from a baseline historical failure rate that is subsequently adjusted to

reflect the anticipated impact on failure of specific line attributes. Baseline failure rate

estimates are obtained from statistical analysis of historic pipeline incident data. These

baseline rate estimates are converted to line-specific estimates using failure rate adjustment

factors that depend on the values of a set of key attributes. The mode of failure is taken into

account by multiplying the adjusted total failure rate estimate by a mode factor that

represents the relative likelihood of failure by small leak, large leak and rupture.

For models directly linked to a baseline historical failure rate, the annual failure rate estimate,

, for each attribute-consistent section of line, as a function of failure mode iand failure

causej, is given by

ijfR

[A.1a]jijjij FFfbf

AMRR =

where = the baseline failure rate for failure causej;

= the relative probability of failure by mode ifor failure causej; and

= the failure rate modification factor for failure causej.

jfbR

ijFM

jFA

For models not directly linked to a baseline historical failure rate (see Section A.3), the

annual failure rate estimate for each section of line is given by

[A.1b]ijjij Fff

MRR =

where = the failure rate for failure causej.jf

R



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A.2 Historical-Based Probability Estimation for Onshore Pipelines

A.3 Baseline Failure Rates

The failure rate is defined as the annual number of incidents involving loss of containment

divided by the length of pipeline in operation for the year in which incidents are reported.

The baseline failure rate, Rfb, is defined herein as the average failure rate for a reference

pipeline section associated with a particular pipeline system, operating company or industry

sector. It is intended to reflect typical conditions relating to construction, operation and

maintenance for lines where the failure cause of interest constitutes a significant integrity

threat. Note that the reference pipeline can and will be different for different failure causes

(e.g. the attributes of a line where SCC constitutes a significant failure hazard may not be

typical of pipelines where internal corrosion is a significant failure hazard).

For a given pipeline system the baseline failure rate estimates are best obtained from

operating company data if the system exposure (i.e. the total length and age of the system) is

sufficient to yield a statistically significant number of failure incidents. In the absence of

appropriate company or system specific data, an estimate of the baseline failure rates can be

obtained from historical incident and exposure data gathered and published by government

regulatory agencies, industry associations, and consultants.

A review of onshore pipeline incident data and statistical summary reports was carried out to

facilitate the development of a set of reference failure rates (and corresponding reference

pipeline attributes) that could be assumed to apply to the population of natural gas, crude oil

and petroleum product pipelines as a whole. Allowing for differences in incident reporting

requirements associated with different reporting agencies, and recognizing that in the context

of the risk estimation approach adopted herein, we are interested in rate estimates that

include small leaks, which are often not reported, the review supports the baseline failure

rates summarized in Table A.1.

Failure Cause Failure Rate (per km yr)

External Metal Loss Corrosion 3.0 x 10-4

Internal Metal Loss Corrosion (simplified | refined) 3.0 x 10-4

| 2.5 x 10-2

Mechanical Damage 3.0 x 10-4

Geotechnical Hazards N/A

Stress Corrosion Cracking 3.0 x 10-4

Manufacturing Cracks (seam weld fatigue) N/A

Seismic Hazards N/A

Other (excluding mechanical components) 2.0 x 10-4

Table A.1 Baseline Failure Rates for Onshore Pipelines

Note that baseline rates are not tabulated for failure causes involving geotechnical hazards,

seismic hazards and manufacturing cracks. This reflects the fact that these failure causes are

highly location or line specific (as opposed to being a common problem) and the associated

failure rates are therefore not adequately characterized using the adjusted baseline failure rate

approach described above. Instead, an approach to failure rate estimation that keys on



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Historical-Based Probability Estimation for Onshore Pipelines A.3

specific attributes of the line in question is be employed for these failure causes. The specific

approach adopted for each of these excepted failure causes will be described in the sections

of the report devoted to their respective failure rate models.

A.4 Failure Mode FactorThe relative probability of failure by small leak, large leak, or rupture will depend on the

failure mechanism being considered. For example, metal loss corrosion failures are

predominantly small leaks (i.e. pin holes) whereas mechanical damage failures caused by

excavation equipment typically involve a greater percentage of large leaks and ruptures.

In PIRAMID, the distinction between the three failure modes is tied to the hole size, or more

explicitly, the equivalent circular hole diameter. Pipeline failure rate summaries that report

failure mode data by equivalent hole size (e.g. Fearnehough 1985, and EGIG 1999) typically

define the transition from small leak to large leak by an equivalent hole diameter of 20 mm,

and the transition between large leak and rupture by an equivalent diameter ranging from

80 mm (Fearnehough 1985) to the line diameter (EGIG 1999). Based on this approach tofailure mode distinction, the above references suggest relative failure mode probabilities for

gas transmission pipelines in the following ranges:

Corrosion -85 to 95% small leaks, 5 to 10% large leaks and 0 to 5% rupture

External interference -20 to 25% small leaks, 50 to 55% large leaks and 20 to 25% rupture

Ground movement -10 to 20% small leaks, 35 to 45% large leaks and 35 to 45% rupture

Construction/Material Defects -55 to 70% small leaks, 25 to 35% large leaks and 5 to 10% rupture

Other causes/unknown -70 to 90% small leaks, 5 to 15% large leaks and 5 to 15% rupture

Note that stress corrosion cracking is not specific addressed in these summary reports,

however, anecdotal information on the North American experience suggests that most

failures are large leaks or ruptures.

The earthquake loss estimation methodology developed by the US Federal Emergency

Management Agency (FEMA 1999) assumes that damage due to seismically induced

permanent ground movement will consist of 20% leaks and 80% breaks.

Representative failure mode splits based on the above information, assuming that the

behaviour of gas and liquid product pipelines at failure is comparable, are summarized in

Table A.2.



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Failure ModeFailure Cause

Small Leak Large Leak Rupture

External and Internal Corrosion 85 % 10 % 5 %

Equipment Impact 25 % 50 % 25 %

Geotechnical Hazards 20 % 40 % 40 %

Stress Corrosion Cracking 0 % 50 % 50 %

Manufacturing Cracks (seam weld fatigue) 60 % 30 % 10 %

Seismic Hazards 0 % 20 % 80 %

Other Causes 80 % 10 % 10 %

Table A.2 Reference Failure Mode Splits for Onshore Pipelines

A.5 Failure Rate Models and Attribute Modification Factors

The algorithms that define the failure rate modification factor,AF, for models that depend onbaseline historical failure rates, and the algorithms that define the failure rate,Rf, for models

that do not depend on baseline historical failure rates, are described in the following sections.

A.5.1 External Corrosion

Pipeline failure associated with external metal loss corrosion is typically the result of a loss

of pipe protection at locations where the surrounding soil environment supports a corrosion

reaction. The factors that affect the susceptibility of a line to external corrosion include: the

type and condition of the coating system; the level of cathodic protection; and the corrosivity

of the surrounding soil medium. Also, the operating temperature of the pipeline affects the

corrosivity of the environment and the general condition of the coating system because hightemperatures promote coating decay and accelerate chemical reactions. Because external

corrosion is a time dependent mechanism, the extent of corrosion damage and its propensity

to cause line failure will be significantly influenced by the duration of exposure (i.e. the line

age) and the thickness of the pipe wall that must be penetrated by a growing corrosion

feature. The specific line attributes used in this model are listed in Table A.3.



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Attribute NameUnits

Metric (Imperial)Attribute Description

Benefit Period of Hydrotest - External

Corrosionyears

The length of time over which a hydrostatic pressure

test event is assumed to provide a reduction in the

failure rate due to external corrosion.

Benefit Period of Inspection - External

Corrosionyears

The length of time over which an inspection andmaintenance event is assumed to provide a reduction

in the failure rate due to external corrosion.

Casing Short Choice

An indication of whether electrical shorting at cased

locations is contributing to a lack of effective cathodic

protection at exposed locations on the pipe wall.

Cathodic Protection Level Choice

A characterization of the adequacy and uniformity of

the voltage potential generated by the cathodic

protection system.

Coating Condition ChoiceA characterization of the integrity of the external coating

system.

Coating Type Choice The type of external coating applied to the pipeline.

Date of External Coating Rehabilitation YYYY/MM/DDThe date when the external coating system was

replaced or otherwise rehabilitated.

Date of Installation YYYY/MM/DD The date when the pipeline was installed.

Date of Last Hydrotest YYYY/MM/DDThe date when the most recent hydrostatic pressure

test was performed.

Date of Last Inspection - External

CorrosionYYYY/MM/DD

The date when the most recent inspection and

maintenance event having an effect on internal

corrosion was performed.

Effectiveness of Inspection - External

Corrosion%

The reduction in the failure rate due to external

corrosion resulting from the most recent inspection and

maintenance event.

Electrical Interference Choice

An indication of whether or not stray electrical currents

are undermining the effectiveness of cathodic

protection at exposed locations on the pipe wall.

Product Temperature C (F)

The average temperature of the product being

transported through the line. (Note that pipe body

temperature is assumed to be equal to the product

temperature.)

Soil Corrosivity Choice

A characterization of the degree to which the soil

conditions surrounding the pipe provide an environment

that is conducive to the development of metal loss

corrosion in unprotected areas of pipe.

Wall Thickness mm (in) The nominal wall thickness of the line pipe.

Table A.3 Line Attributes Required by External Corrosion Model

The failure rate modification factor developed to reflect the impact of these factors on the

baseline external corrosion failure rate is



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( ) CFCPSCec

ECF FFFTt

KA

+=

28.2*

8.17

[A.2]

where KEC = external corrosion model scaling factor;

= effective line age for external corrosion (see Section A.6);t = wall thickness;

T = operating temperature (assumed equal to product temperature);

F

*

ec

SC = soil corrosivity factor;

FCP = cathodic protection factor; and

FCF = coating factor.

The core relationship involving the line age wall thickness tand operating temperature Twas developed from a multiple linear regression analysis of failure rate data on hydrocarbon

liquid pipelines operating in California published by the California State Fire Marshall

(CSFM 1993). It should be noted that the actual relationship derived from the California

pipeline incident data involved line diameter rather than wall thickness. The diameter termwas translated into a wall thickness term (which, in the context of corrosion failure, is

considered to be the more relevant parameter) by assuming that on average wall thickness is

directly proportional to line diameter.

The soil corrosivity factorFSCis an index that scales the rate modification factor over a range

that reflects the impact of variations in soil corrosivity on the corrosion failure rate. The

index multipliers associated with each value of the soil corrosivity attribute are given in

Table A.4.

Soil

Corrosivity

Resistivity

(ohm cm)

Soil Drainage and Texture FSC

Very low > 10,000 excessively drained - coarse texture 0.33

Low 5000 - 10,000well drained - moderately coarse texture, or

poorly drained - coarse texture0.67

Moderate 2000 - 5000

well drained - moderately fine texture, or

poorly drained - moderately coarse texture, or

very poorly drained with high steady water table

1.0

High 1000 - 2000

well drained - fine texture, or

poorly drained - moderately fine texture, or

very poorly drained with fluctuating water table

2.3

Very high < 1000 poorly drained - fine texture, ormucks, peats with fluctuating water table

3.3

Table A.4 Soil Corrosivity Factor

The order of magnitude range was established based on the results of corrosion metal loss

tests conducted on steel pipe samples buried in soils of various resistivities as reported by

Crews (1976). The corrosivity categories and corresponding resistivity ranges (with



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descriptions of characteristic soil drainage and texture) were adapted from those developed

by Miller et al. (1981) as a basis for ranking the underground corrosion potential based on

soil surveys.

The cathodic protection factorFCPis an index that scales the rate modification factor over a

range that reflects the impact of varying degrees of cathodic protection system effectivenesson corrosion failure rate. The index multipliers associated with each value of the cathodic

protection level attribute are given in Table A.5.

Cathodic Protection Level Characterization FCP

Consistently within range adequate voltage, uniform level 0.5

Isolated excursions adequate average voltage, some variability 1.0

Extensive excursions inadequate voltage and/or high variability 2.0

None 5.0

Table A.5 Cathodic Protection Factor

The order of magnitude range was established primarily based on failure rate data reported

by the CSFM (1993) that indicates a failure rate approximately five times higher for

unprotected pipe. The multipliers 0.5 and 2.0 were introduced based on judgement to reflect

the fact that the five fold reduction in failure rate is an average value which therefore applies

to pipelines having average cathodic protection levels and that some allowance should be

made for above and below average conditions.

Note that the impact of two additional line attributes, the presence of casing shorts and

electrical interference, are tied to the cathodic protection factor. The assumption implicit inthe model is that if there is a casing short, then the cathodic protection factor will be set equal

to the no protection state (FCP= 5.0) and if there is electrical interference, then the cathodic

protection factor will be downgraded by one category.

The coating factorFCFis an index that scales the rate modification factor to reflect the impact

of different coating types and their condition on corrosion failure rate. The index multipliers

associated with each combination of coating type and coating condition are given in

Table A.6.



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Coating Type FCF

Coating

Condition

Completely

sound

Isolated

damage

Extensive

damage

Not applicable

(no coating)

Fusion bonded epoxy 0.25 0.5 1.0 1.0

Extruded polyethylene 0.25 0.5 1.0 1.0

Coal tar 0.5 1.0 2.0 2.0

Wax and vinyl tape 1.0 2.0 4.0 4.0

Asphalt 1.0 2.0 4.0 4.0

Polyethylene tape 1.0 4.0 8.0 8.0

Bare (no coating) 8.0 8.0 8.0 8.0

Table A.6 Coating Factor

The coating related index multipliers in Table A.6 were adapted from a study byKiefner et al. (1990) wherein factors are cited based on the perceived track record of

generic coating types.

The model scale factorKECserves to adjust the failure rate modification factor to a value of

unity for the external corrosion reference sectiondefined as the line section associated with

the reference value of all line attributes that influence the external metal loss failure rate

estimate. The intention is that the baseline failure rate for external corrosion should apply

directly to the reference section (hence the need for a corresponding attribute modification

factor of 1).

The expression forKECis obtained by first rearranging Equation [A.2] and settingAF= 1.0 togive

( ) CFCPSCec

EC

FFFTt

K

8.17

1

28.2*

+

=

[A.3]

The value of the model scale factor is calculated using Equation [A.3] by substituting the

values of all parameters that are associated with the reference section. The reference section

parameter values should be developed in conjunction with the baseline failure rate estimate

(see Section A.3) on a pipeline system, operating company or industry basis, depending onthe intended application of the model.

Based on a review of incident data summaries in the public domain the following attribute

values are considered to be representative of the external corrosion reference section:



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Age = 38 years;

Coating type = Coal tar;

Coating condition = Isolated damage;

Cathodic protection level = Isolated excursions;

Product (operating) temperature = 25 C; Soil corrosivity = Moderate; and

Wall thickness = 5.82 mm.

The corresponding model scale factor isKEC= 2.92 x10-5

.

A.5.2 Internal Corrosion

A.5.2.1 Overview

Pipeline failure associated with internal metal loss corrosion is primarily influenced by the

corrosivity of the transported product and the product flow conditions. Like externalcorrosion, internal corrosion is a time dependent mechanism. The extent of corrosion

damage and its propensity to cause line failure will therefore be significantly influenced by

the duration of exposure (i.e. the line age) and the thickness of the pipe wall that must be

penetrated by a growing corrosion feature.

Two models are available for estimating internal corrosion failure rates; a so-called

simplified model in which the product corrosivity is defined directly by a single line

attribute; and a refined model in which the product corrosivity, as represented by the metal

loss rate, is calculated from a set of line attributes that reflect specific characteristics of the

product and product flow regime. Use of the simplified model places the responsibility on

the user to accurately characterize product corrosivity whereas use of the refined model

requires significantly more pipeline-specific information.

Note that the refined model is intended to address CO2corrosion of either liquid multiphase

flow, using a corrosion rate model developed by Gopal and Jepson (1996); or wet gas flow,

based on a model by de Waard et al. (1991). The refined model does reflect the impact of

H2S content on corrosion rates but it does not address other internal corrosion mechanisms

(e.g. microbial induced corrosion or MIC) because their characteristics can be extremely line-

specific and they fall beyond the scope of this model. Note also that neither model accounts

for the effects of internal pipe coatings or liners.

A.5.2.2 Simplified Model

The specific line attributes used in the simplified internal metal loss corrosion model are

listed in Table A.7.



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Attribute NameUnits


Benefit Period of Hydrotest - Internal

Corrosionyears



failure rate due to internal corrosion.

Benefit Period of Inspection - Internal

Corrosionyears


in the failure rate due to internal corrosion.



test was performed.

Date of Last Inspection - Internal

CorrosionYYYY/MM/DD


maintenance event having an effect on internal

corrosion was performed.

Effectiveness of Inspection - Internal

Corrosion%

The reduction in the failure rate due to internal

corrosion resulting from the most recent inspection and

maintenance event.

Product Corrosivity ChoiceA characterization of the corrosivity of the product

mixture.


Table A.7 Line Attributes Required by Internal Corrosion Model (simplified method)


baseline internal metal loss failure rate is

PC

ic

ICF FtKA

*

=

[A.4]

where KIC = internal corrosion model scaling factor;

= effective line age for internal corrosion (see Section A.6);

t = wall thickness; and

F

*

ic

PC = product corrosivity factor.

The core relationship involving line age and wall thickness twas inferred from the modeldeveloped for external corrosion which suggests that the failure rate is directly proportional

to line age and inversely proportional to wall thickness. Note that the line operating

temperature term in the external corrosion model was dropped because the effect oftemperature on the failure rate is to be covered under the broadly defined measure of product

corrosivity.

The product corrosivity factorFPCis an index that scales the rate modification factor over a

range that reflects the impact of variations in product corrosivity on corrosion failure rate.

The index multipliers associated with each value of the product corrosivity attribute are given

are given in Table A.8.



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Product CorrosivityGrow Rate

(mm/yr)Index

Very low < 0.02 0.04

Low 0.02 to < 0.1 0.2

Moderate 0.1 to < 0.5 1.0

High 0.5 to < 2.5 5.0

Extreme 2.5 25.0

Table A.8 Product Corrosivity Factor

The index range was established based on the simple assumption that if the corrosion growth

rate is essentially constant, and failure rate has been shown to be inversely proportional to

wall thickness, then it follows that the failure rate will be directly proportional to pit depth

growth rate. The index multipliers are therefore directly proportional to the assumed growth

rates for each product category. The corrosion growth rate ranges associated with eachproduct category are consistent with values that are generally accepted in the process piping

industry.

The model scale factorKICserves to adjust the failure rate modification factor to a value of

unity for the internal corrosion reference sectiondefined as the line section associated with

the reference value of all line attributes that influence the internal metal loss failure rate

estimate. The intention is that the baseline failure rate for internal corrosion should apply

directly to the reference segment (hence the need for a corresponding attribute modification

factor of 1). The expression for KIC is obtained by first rearranging Equation [A.4] and

settingAF= 1.0 to give

1*

PC

ic

IC

Ft

K

=

[A.5]




(see Section A.3) on a pipeline system, operating company or industry basis, depending on

the intended application of the model.


values are considered to be representative of the internal corrosion reference section:

Age = 38 years;

Product corrosivity = Moderate; and

Wall thickness = 5.82 mm.



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The corresponding model scale factor isKIC= 1.53 x10-1

.

A.5.2.3 Refined Model

A.5.2.3.1 Liquid Product Corrosion

The specific line attributes used in the refined internal metal loss corrosion model for liquid

multiphase flow are

Attribute NameUnits



Corrosionyears

The length of time over which a hydrostatic pressuretest event is assumed to provide a reduction in thefailure rate due to internal corrosion.


Corrosionyears

The length of time over which an inspection andmaintenance event is assumed to provide a reductionin the failure rate due to internal corrosion.


Date of Last Hydrotest YYYY/MM/DDThe date when the most recent hydrostatic pressuretest was performed.


CorrosionYYYY/MM/DD

The date when the most recent inspection andmaintenance event having an effect on internalcorrosion was performed.

Diameter mm (in) The nominal outside diameter of the line pipe.


Corrosion%

The reduction in the failure rate due to internalcorrosion resulting from the most recent inspection andmaintenance event.

Inhibitor Effectiveness %

The reduction in the rate of internal corrosionattributable to the use of inhibitors in the productmixture.

Liquid Flow Characterization ChoiceA characterization of the liquid phase flow (areas of

liquid separation or stagnation) in the product mixture.

Liquid Fraction Water-Cut RatioThe ratio of water volume to total liquid volume for theproduct mixture.

Operating Pressure Gradient kPa/km (psi/mi)The pressure gradient driving the product mixturethrough the pipeline.

Partial Pressure CO2 kPa (psi)

The concentration of dissolved CO2 in the productmixture, expressed as a partial pressure calculatedbased on mole fraction.

Partial Pressure H2S kPa (psi)

The average concentration of dissolved H2S in theproduct mixture, expressed as a partial pressurecalculated based on mole fraction.


The average temperature of the product beingtransported through the line. (Note that pipe bodytemperature is assumed to be equal to the product

temperature.)Wall Thickness mm (in) The nominal wall thickness of the line pipe.

Table A.9 Line Attributes Required by the Liquid Product Internal Corrosion Model (refined method)



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The liquid product failure rate modification factor developed to reflect the impact of key

factors on the baseline internal metal loss failure rate is

inhibitSHoilo

ic

ICLF FFFVt

KA2

*

=

[A.6]

whereKICL = liquid product internal corrosion model scale factor;


t = wall thickness;

V

*

ic

0 = basic corrosion rate;

Foil = liquid hydrocarbon factor;

FH2S = hydrogen sulfide factor; and

Finhibit = inhibitor factor.

The basic corrosion rate is calculated using an empirically derived model for full pipe flow

developed by Gopal and Jepson (1996). This model estimates the corrosion rate as a functionof total wall shear stress, CO2partial pressure, and temperature. It is given by

1.0

83.0

2)15.273(

5041

1000)15.273(416649 w

T

o

pCOeTV

+=

+

[A.7a]

where T = product temperature (C);

pCO2 = carbon dioxide partial pressure (kPa); and

w = wall shear stress (N/m2).

The wall shear stress is given by

slopew PD

4000= [A.7b]

where Pslope = operating pressure gradient = P/L (kPa/km); andD = diameter (mm).

This basic corrosion rate model is only applicable to pipelines under full pipe flow

conditions. In general, corrosion rates for slug flow conditions are much higher than those

for full pipe flow. It has been suggested (Gopal and Jepson 1996) that this is caused by the

stripping of poorly adhered layers of corrosion products due to a combination of high wallshear stress and turbulence under slug flow conditions.

The liquid hydrocarbon factor, Foil, is intended to account for the potential protection

afforded to the pipe surface by the liquid hydrocarbon phase. The index multiplier associated

with relevant line attributes is given in Table A.10. The model underlying this factor

assumes that internal corrosion can only occur when the interior pipe surface is wetted. It

further assumes that the water phase can wet the pipe surface if the water cut is greater than



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or equal to 0.3, or if flow conditions allow the water to separate from the liquid hydrocarbon.

Note that separation is considered likely for flow velocities less than 1.0 m/s but it can also

occur in bent or non-horizontal pipe at higher flow velocities.

Foil No separation/stagnation Separation/stagnation

Water cut< 0.3 0.0 1.0

Water cut>= 0.3 1.0 1.0

Table A.10 Liquid Hydrocarbon Protection Factor

The hydrogen sulfide factor,FH2S, is an index that adjusts the failure rate modification factor

to acknowledge the potential two-fold increase in corrosion rate caused by the presence of

hydrogen sulfide (Videm 1995). The factor indices are shown in Table A.11.

H2S Partial Pressure (pH2S) FH2S

pH2S0.056 kPa 1.0

pH2S> 0.056 kPa 2.0

Table A.11 Hydrogen Sulfide Factor

The inhibitor factor, Finhib, scales the failure rate based on the assumed effectiveness of the

inhibitor used in the pipeline. Inhibitor effectiveness is defined in terms of the expected

reduction in metal loss corrosion rate. The factor is given by

1000.1E

Finhib = [A.8]

whereEis the inhibitor effectiveness (in percent).

The model scale factorKICLserves to adjust the failure rate modification factor to a value of

unity for the internal corrosion reference sectiondefined as the line section associated with

the reference value of all line attributes that influence the internal metal loss failure rate

estimate. The intention is that the baseline failure rate for internal corrosion should apply

directly to the reference segment (hence the need for a corresponding attribute modification

factor of 1). The expression forKICLis obtained by rearranging Equation [A.6] and setting

AF= 1.0 to give

inhibitSHoiloic

ICLFFFV

tK

2

0.1*

=

[A.9]





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Based on three case studies by Jones et al. (1998) and a review of other literature the

following attribute values are used to define the liquid product reference section:

Age = 14 years;

Diameter = 610 mm,

Inhibitor Effectiveness = 0 % (No Inhibitor)

Liquid Flow Characterization = No separation/stagnation

Liquid Fraction Water-Cut = 0.33 (ratio)

Operating Pressure Gradient = 42.84 kPa/km

Partial Pressure - C02 = 114.2 kPa

Partial Pressure - H2S = 0.0 kPa Product Temperature = 23. 9 C

Wall Thickness = 11.91 mm

The corresponding model scale factor isKICL= 0.8165.



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A.5.2.3.2 Wet Gas Corrosion

The specific line attributes used in the refined internal metal loss corrosion model for wet-gas

flow are

Attribute Name UnitsMetric (Imperial)

Attribute Description


Corrosionyears

The length of time over which a hydrostatic pressuretest event is assumed to provide a reduction in thefailure rate due to internal corrosion.


Corrosionyears

The length of time over which an inspection andmaintenance event is assumed to provide a reductionin the failure rate due to internal corrosion.

Condensation Rateg/(m

2s)

(1E-6lb/(ft2s))

The rate of condensation of the transported watervapour.


Date of Last Hydrotest YYYY/MM/DDThe date when the most recent hydrostatic pressuretest was performed.


CorrosionYYYY/MM/DD

The date when the most recent inspection andmaintenance event having an effect on internalcorrosion was performed.


Corrosion%

The reduction in the failure rate due to internalcorrosion resulting from the most recent inspection andmaintenance event.

Inhibitor Effectiveness %

The reduction in the rate of internal corrosionattributable to the use of inhibitors in the productmixture.

Liquid Flow Characterization ChoiceA characterization of the liquid phase flow (areas ofliquid separation or stagnation) in the product mixture.

Liquid Fraction Water-Cut RatioThe ratio of water volume to total liquid volume for theproduct mixture.

Partial Pressure CO2 kPa (psi)

The concentration of dissolved CO2 in the product

mixture, expressed as a partial pressure calculatedbased on mole fraction.

Partial Pressure H2S kPa (psi)

The average concentration of dissolved H2S in theproduct mixture, expressed as a partial pressurecalculated based on mole fraction.

pH pH The acidity of the product water-cut.

Pressure Profile kPa (psi)

The anticipated maximum operating pressure in thepipeline defined at the start and end of the line and atselected reference points along the length of the line.(Note that the location of intermediate points should bechosen to adequately characterize the pressure profilegiven that the program uses linear interpolation to inferthe line pressure at all locations between specifiedreference points. Note also that the specified pressureshould reflect an upper bound pressure profile

associated with likely worst case operating conditionsincluding, for example, periodic line pack or shut in.)


The average temperature of the product beingtransported through the line. (Note that pipe bodytemperature is assumed to be equal to the producttemperature.)


Table A.12 Line Attributes Required by the Wet-Gas Internal Corrosion Model (refined method)



19/50


The wet-gas failure rate modification factor developed to reflect the impact of key factors on

the baseline internal metal loss failure rate is

inhibitcondoilpHscaleSHo

ic

ICGF FFFFFFVt

KA2

*

=

[A.10]

whereKICG = wet-gas internal corrosion model scale factor;


t = wall thickness;

V

*

ic

0 = basic corrosion rate;

FH2S = hydrogen sulfide factor;

Fscale = protective film factor;

FpH = pH factor;

Foil = liquid hydrocarbon factor;

Fcond =.condensation factor; and

Finhibit = inhibitor factor.

The basic corrosion rate prediction and adjustment factors, with the exception of FH2S and

Finhibit, are based on a model developed by deWaard et al. (1991). This model has been

updated in recent years; however, the basic equations have not changed. The 1991 version

has been used because it is completely in the public domain and later versions of the model

reported in the literature do not include empirically derived constants. The basic corrosion

rate is given by

)0.100log(67.015.273

17108.5)log( 2fCO

TVo +

+= [A.11a]

where: T = product temperature (C); and

fCO2 = carbon dioxide fugacity (kPa).

Note that carbon dioxide fugacity is to calculate the basic corrosion rate instead of the CO2

partial pressure because fugacity accounts for both the total pressure of CO2 in the system

and the activity of CO2in the presence of other gases. Fugacity is given by

[A.11b]apCOfCO 22 =

where:pCO2 = carbon dioxide partial (kPa); and

a = fugacity coefficient.

The fugacity coefficient is based on results reported by deWaard for the fugacity of a binary

gas system consisting of CO2 and CH4, as calculated using methods described by

Lammers (1973).



20/50


The protective film factor, Fscale, is used to adjust the basic corrosion rate (and failure rate

modification factor) to account for the formation of a protective film at higher temperatures.

The corrosion product film changes texture with temperature and at temperatures below

approximately 60 C the film is easily removed by flowing liquids. With increased

temperature the protective film is more protective and more resistant to erosion.

The protective film factor is given by the following

+

+=

15.273

0.1

15.273

0.12400)log(

scale

scaleTT

F

.1scaleF

and [A.12a]

0 [A.12b]

where T is the product temperature and Tscaleis the scaling temperature given by

15.273)log(6.07.6

2400

2

+

=fCO

Tscale [A.12c]

The presence of H2S is assumed to interfere with the formation of a stable protective scale

(Srinvasan 1999); so in situations where the H2S partial pressure is greater than zero the

protective film factorFscaleis set to 1.0.

The pH factor,FpH, is given by

forpH( actsatpH pHpHF = 32.0)log( )

)

sat>pHact; [A.13a]

0 forpH.1=pHF sat=pHact; [A.13b]

forpH( 6.113.0)log( satactpH pHpHF = sat


21/50


The condensation factor,Fcond, accounts for the decrease in corrosion rate that occurs in the

presence of condensing water. It is given by

[A.15a]condcond rF 4.0=

Fcond


22/50


Based on a three case studies by Jones et al. (1998) and a review of other literature the

following attribute values are used for the wet-gas refined internal corrosion reference

section:

Age = 14 years;

Condensation Rate = 0.25 g/m2

s; Inhibitor Effectiveness = 0 %;

Liquid Flow Characterization = No separation/stagnation;

Liquid Fraction Water-Cut = 0.33 (ratio);

Partial Pressure - C02 = 62.05 kPa;

Partial Pressure - H2S = 0.0 (no H2S);

pH = 5.5 pH;

Pressure = 6205.3 kPa;

Product Temperature = 23. 9 C; and

Wall Thickness = 11.91 mm.

The corresponding model scale factor isKICG= 2.9950.

A.5.3 Equipment Impact

A.5.3.1 Overview

Mechanical damage incidents are typically caused by construction or excavation equipment

working in the area of the pipeline. The potential for line failure due to damage inflicted by

this type of equipment depends on both the likelihood of equipment impact and the

subsequent likelihood of pipe failure given impact. The factors that affect the susceptibility

of a line to equipment impact include: 1) the level of construction/excavation activity on or

near the right-of-way, and 2) the degree to which line burial depth, right-of-way condition

and signage, one-call systems, and line patrols reduce the potential for impact given activity.

The potential for line failure given interference will depend on the type of equipment

involved in the incident (i.e. the level of force applied and the configuration of the indentor)

and the resistance of the pipe to a puncture-type failure, which is largely dependent on the

thickness of the pipe wall and the strength of the material. The specific line attributes used in

this model are listed in Table A.13.



23/50


Attribute NameUnits


Activity Zone Choice

A category describing the relative frequency of

occurrence of excavation activity on the right-of-way

and an indication of the likely nature of the activity (with

shallow excavations being associated with

undeveloped areas and deep excavations being

associated with developed or developing areas).

Alignment Markers - Above Ground Choice

An indication of whether or not permanent above

ground markers (such as fencing or concrete curbs)

exist to provide an obvious indication of the location of

the pipeline alignment.

Alignment Markers - Buried Choice

An indication of whether or not buried markers (such as

coloured tape) exist to provide an indication of the

location of the pipeline alignment after the start of

excavation activity.

Alignment Markers - Explicit Signage Choice

An indication of the placement of explicit signage that

describes and locates the pipeline and provides atelephone number for dig notification.

Crossings / Special Terrain ChoiceA characterization of the type of crossing or special

terrain feature encountered by the pipeline.

Depth of Burial m (ft) The depth of top of the pipeline below ground surface.


Dig Notification Requirement Choice

The legislative requirements pertaining to the need for

parties planning excavation activities to use a one-call

system.

Dig Notification Response ChoiceThe action taken by the operator in response to a dig

notification.

Mechanical Protection Choice

An indication of whether or not buried physical

protection (such as concrete slabs or steel plates)

exists to effectively prevent direct contact between the

pipe body and any excavation equipment.

One-call System Type Choice The type of one-call system in place.

Public Awareness Level Choice

An assessment of the relative level of public awareness

regarding the presence of, and hazards posed by,

buried pipelines.

Right-of-way Indication Choice

An assessment of the degree to which the overall

condition of the right-of-way provides an indication of

the existence of a buried pipeline in the immediate

area.Surveillance Interval Choice The time interval between right-of-way patrols.

Surveillance Method Choice The method employed to patrol the right-of-way.


Yield Strength (SMYS) MPa (ksi)Specified minimum yield strength of the line pipe. (e.g.

5XL60 should be reported as 60 ksi or 414 MPa)

Table A.13 Line Attributes Required by Equipment Impact Model



24/50


The failure rate modification factor developed to reflect the influence of these factors on the

baseline equipment impact failure rate is

[A.18]HFHITMDF PRKA |=

where RHIT is the rate of occurrence of equipment impact events, PF|H is the probability offailure given impact, andKMDis the model scaling factor.

A.5.3.2 Rate of Occurrence of Equipment Impact

The rate of occurrence of equipment impact events is estimated using an algorithm developed

using so-called fault tree analysis techniques. The algorithm takes the form

15,321 ..., BBBBHIT pppfrR = [A.19]

where rB1is the rate of excavation-related activity on the alignment (in events per unit length

per year) andpBiis the probability of occurrence of basic event Bi, where each basic event isdefined as the possible outcome of actions that can be shown to depend on physical

characteristics of the pipeline and its right-of-way, and various operating and preventative

maintenance practices employed by the operator. The basic events that are assumed to

contribute to the potential for a line hit, and the line attributes that are assumed to influence

each basic event probability are:

Equipment activity on the alignment(activity zone and crossings);

Parties fail to use one-call before moving onto right-of-way(public awareness level, dignotification requirement and one-call system type);

Right-of-way indicators not recognized(public awareness level and right-of-way

indication); Parties ignore right-of-way indications(public awareness level and one-call system

type);

One-call system fails to notify operator(one-call system type);

Explicit signage not seen(public awareness level and alignment markers-explicitsignage);

Parties ignore explicit signage(public awareness level);

No patrol during period of activity(surveillance interval);

Patrol personnel fail to detect activity(surveillance method);

Operator fails to ensure correct location of alignment(dig notification response);

Above ground markers fail to convey alignment location(alignment markers aboveground);

Buried markers fail to convey alignment location(alignment markers buried);

Accidental activity of located alignment(dig notification response);

Excavation depth exceeds burial depth(land use and depth of burial); and

Mechanical protection fails to protect pipe(mechanical protection).



25/50


The hit frequency algorithm outlined above is common to both the historical-based and the

reliability-based probability estimation models that have been developed for equipment

impact. See Appendix D, Section D.2.1 for a detailed description of the hit frequency model.

A.5.3.3 Probability of Failure Given Impact

Given a mechanical interference event, the probability of failure, PF|H, is equal to the

probability that the load,L, will exceed the pipe wall resistance,R, at the location of impact.

This can be written as

[A.20]( ) ( 0| = LRPRLPP HF )

If, as a first order approximation, the uncertainty associated with both the applied load and

the pipe resistance are characterized by assuming that both parameters are normally

distributed then a solution to Equation [A.20] is given by

( )P P R LF HL R

L R

| = < =

+

0 2 2

[A.21]

where L = the mean value of the applied load;

L = the standard deviation of the applied load;

R = the mean value of the pipe resistance;

R = the standard deviation of the pipe resistance;

and is the standard normal distribution function.

The magnitude of the applied load is a function of the weight of the construction/excavation

equipment impacting the pipeline. Based on an estimate of the weight distribution of

excavators operating in North America obtained by C-FER from industry, and assuming that

the impact force in kN is equal to 5.63 times the excavator weight in tonnes

(Spiekhout 1995), the applied load can be characterized by the following

L= 164 kN, [A.22a]

L= 73.8 kN [A.22b]

The pipe body resistance (i.e. the indentor load to cause failure) can be estimated using asemi-empirical model developed by Driver and Playdon (1997) from full-scale tests on line

pipe reported in the literature. The model takes the form

( ) up twLt

DR +

= 0029.017.1 [A.23]



26/50


where D = pipe diameter (mm);

t = pipe wall thickness (mm);

L = indentor length (mm);

w = indentor width (mm); and

u = pipe body ultimate tensile strength (MPa).

Driver and Playdon suggest that a representative indentor has a length of 70 mm and a width

of 5 mm, which corresponds to the geometry of an individual tooth on the bucket of a typical

excavator.

From an analysis of line pipe material property data reported by Fleet Technology Limited

(1996), a relationship between the pipe body tensile strength and the yield strength Sis given

by

7786.0832.4 Su = [A.24]

Substituting this expression for the tensile strength in Equation [A.23] gives the followingexpression for the indentor load causing failure in terms of the material yield strength

( ) 7786.00029.017.183.4 StwLt

DRp +

= [A.25]

Uncertainty in estimating puncture resistance is taken into accounted by incorporating two

model uncertainty factors in the final expression for the pipe body resistance, R, which is

given by

R C R CP= +1 2 [A.26]

where C1 and C2 are the multiplicative and additive components of the model error,

respectively. Regression analysis of test-to-predicted ratios by Driver and Playdon using

Equation [A.23] reportedly found that C1is best approximated by a constant with a value of

1.00 and C2 is best approximated by a normally distributed variable with mean value of 0.883

kN and a standard deviation of 26.7 kN.

These model error characterizations have been adopted for pipe resistance estimation using

Equation [A.23], because the additional uncertainty associated with estimating the tensile

strength of the material from its yield strength, using Equation [A.25], is small enough in

comparison to the overall level of model uncertainty to be ignored.

Based on this puncture model, and representative assumptions about the variability in pipe

yield strength it can be shown that the pipe resistance is characterized by

( ) 27786.00029.017.183.4 CSR twL

t

D ++

= [A.27a]



27/50


( ) ( ) 2 22

2

17786.0)7786.0(0029.017.183.4 CSSR twLt

D +

+

=

[A.27b]

where S = mean value of pipe yield strength = 1.1 S;

S = standard deviation of pipe yield strength = 0.07 S;C2 = mean value of C2 = 0.883 kN; and

C2 = standard deviation of C2 = 26.7 kN.

The probability of line failure given impact can therefore be estimated from Equation [A.21]

using Equation [A.22] for the load parameters and Equation [A.27] for the resistance

parameters.

A.5.3.4 Model Scale Factor

The model scale factorKMDserves to adjust the failure rate modification factor to a value of

unity for the equipment impact reference sectiondefined as the line section associated withthe reference value of all line attributes that influence the equipment impact failure rate

estimate. The intention is that the baseline failure rate for equipment impact should apply

directly to the reference section (hence the need for a corresponding attribute modification

factor of 1). The expression for KMD is obtained by first rearranging Equation [A.18] and

settingAF= 1.0 to give

1

|HFHIT

MDPR

K = [A.28]

The value of the equipment impact model scale factor is calculated using Equations [A.19],[A.21], and [A.28] by substituting the values of all parameters that are associated with the

reference section. The reference section parameter values should be developed in

conjunction with the baseline failure rate estimate (see Section A.3) on a pipeline system,

operating company or industry basis, depending on the intended application of the model.


values are considered to be representative of the equipment impact reference section:

Activity zone = Zone 3 (high-undeveloped);

Alignment marker above ground = No;

Alignment marker buried = No;

Alignment marker explicit signage = At selected strategic locations;

Depth of burial = 0.9 m;

Diameter = 305 mm;

Dig notification requirement = Not required (voluntary);

Dig notification response = Locate and mark with no site supervision;



28/50


Mechanical protection = None;

One-call system type = Unified system;

Public awareness level = Average;

Right-of-way indication = Continuous but limited indication;

Surveillance interval = Bi-weekly; Surveillance method = Aerial;

Wall thickness = 5.82 mm; and

Yield strength = 289 Mpa.

The corresponding model scale factor isKMD= 776.7.

A.5.4 Geotechnical Hazards

Pipeline failure can occur as a result of geotechnical hazards involving progressive ground

movement (e.g. subsidence, frost heave, thaw settlement, and slope movement), seismicactivity, and river scour. The potential for line failure depends on both the likelihood of

occurrence of the hazardous event and the severity of the event in terms of its potential to

cause pipe failure. The specific line attributes used in this model are listed in Table A.14.

Attribute Name Units Attribute Description

Failure Potential given Geotechnical

Eventprobability

The probability of pipeline failure given the occurrence

of the prescribed geotechnical loading event.

Geotechnical Hazard Occurrence Rateevents / km yr

(events / mi yr)

The frequency of occurrence of a geotechnical loading

event generating significant outside force on the pipe

body (e.g. ground movement, river scour).

Geotechnical Hazard Occurrence Rate

Changeevents / km yr

(events / mi yr)

The annual rate of change in the frequency ofoccurrence of the prescribed geotechnical loading

event (Note that an occurrence rate change of zero

implies that the occurrence rate remains constant over

time).

Girth Weld Type Choice

The type of pipe joint (i.e. weld vs. mechanical

connection) and a relative indication of joint quality

(with respect to tensile strength and ductility) for welded

joints.

Table A.14 Line Attributes Required by Geotechnical Hazard Model

Failures due to ground movement events are highly location and pipeline specific andtherefore, probability estimation based on historical incident rates adjusted by selected line

attributes is not considered appropriate. An alternative approach based entirely on location

specific information is employed. Specifically, pipeline failure associated with geotechnical

hazards will be addressed by directly specifying estimates of both the probability of

geotechnical loading event occurrence, and the probability of line failure given event

occurrence.



29/50


The failure rate is given by

[A.29a]JNTMFMVf FPRR |*

=

where R = effective annual frequency of event occurrence (see Section A.6)

= +R ; [A.29b]

= fixed component of the annual frequency of event occurrence;

= variable component of the annual frequency of event occurrence;

*

MV

MVR

MVR

( )+ MVMV R

= time since the date of pipe installation (line age); = future time increment;

PF|M = probability of pipe failure given event occurrence; and

FJNT = pipe joint factor

Note that for consistency with other failure cause models the frequency of geotechnical event

occurrence must be defined per unit length of pipe. Specifically, if a geotechnical event is

estimated to have an occurrence frequency of x (events per yr), and the effective length of

pipe potentially involved in the geotechnical event is s (km), then the event occurrence

frequency must be entered as x/s (events per km yr).

The frequency of occurrence of a significant geotechnical event is user defined, however, the

fixed component occurrence rate estimates shown in Table A.15 are provided for guidance.

Subjective characterization Events per yr RMV(events per km yr)

Negligible to very low 0.00001 0.000001/s

Low 0.0001 0.00001/s

Moderate 0.001 0.0001/s

High 0.01 0.001/s

Very high 0.1 0.01/s

Note: s = effective length (in km) of the section of pipe potentially involved in the geotechnical event

Table A.15 Geotechnical Hazard Occurrence Rate Suggested Values

The probability of pipeline failure given event occurrence is also user defined. The estimates

shown in Table A.16 are provided for guidance.

Subjective Characterization PF|M

Low 0.01

Moderate 0.1

High 1.0

Table A.16 Failure Potential Given Event Suggested Values



30/50


The pipe joint factorFJNTis an index that modifies the estimate of the probability of failure

given event occurrence to reflect the impact of weld quality on failure when the expected

failure mode is tensile rupture. The index multipliers associated with each joint type are

given in Table A.17.

Girth Weld Type FJNTHigh quality weld 0.5

Average quality weld 1.0

Poor quality weld 2.0

Mechanical joint 5.0

Table A.17 Pipe Joint Factor for Geotechnical Hazards

The index multipliers associated with each girth weld type were established subjectively

based on judgement to reflect the perceived effect on failure probability of variations in the

strength and ductility of different joint types.

Note that if the geotechnical hazard occurrence rate is specified as a negative number, then it

is assumed that failure will involve compression-induced buckling (typically away from the

joints) in which case the joint factor is not relevant and it is therefore set to 1.0 in the failure

rate calculation.

A.5.5 Stress Corrosion Cracking

Pipeline failure associated with stress corrosion cracking (SCC) is the result of a loss of pipe

protection at locations where the physical and operating conditions of the pipe andsurrounding soil environment supports this form of environmentally induced cracking. The

factors that affect the susceptibility of a line to SCC include: the presence of a soil and

groundwater environment conducive to the formation of SCC in areas where coating damage

and has occurred and cathodic protection is ineffective; a susceptible pipe body material; and

an operating pressure that generates tensile stresses sufficient to promote significant crack

growth. The specific line attributes used in this model are listed in Table A.18.



31/50


Attribute NameUnits


Benefit Period of Hydrotest - SCC Cracks years



failure rate due to stress corrosion cracking.

Benefit Period of Inspection - SCC

Cracksyears


in the failure rate due to stress corrosion cracking.

Date of External Coating Rehabilitation YYYY/MM/DDThe date when the external coating system was

replaced or otherwise rehabilitated.



test was performed.

Date of Last Inspection - SCC Cracks YYYY/MM/DD


maintenance event having an effect on SCC was

performed.


Effectiveness of Inspection - SCC Cracks %

The reduction in the failure rate due to SCC resulting

from the most recent inspection and maintenance

event.

Pressure Profile kPa (psi)

The anticipated maximum operating pressure in the

pipeline defined at the start and end of the line and at

selected reference points along the length of the line.

(Note that the location of intermediate points should be

chosen to adequately characterize the pressure profile

given that the program uses linear interpolation to infer

the line pressure at all locations between specified

reference points. Note also that the specified pressure

should reflect an upper bound pressure profileassociated with likely worst case operating conditions

including, for example, periodic line pack or shut in.)

SCC Potential of Environment Choice

A characterization of the degree to which the soil

conditions surrounding the pipe provide an environment

that is conducive to the development of stress corrosion

cracking in susceptible pipe.

SCC Susceptibility of Pipe Choice

A characterization of the susceptibility of the pipe body

(i.e. metallurgy and surface condition) to the formation

of stress corrosion cracking.


Yield Strength (SMYS) MPa (ksi) Specified minimum yield strength of the line pipe. (e.g.5XL60 should be reported as 60 ksi or 414 MPa)

Table A.18 Line Attributes Required by Stress Corrosion Cracking Model


baseline SCC failure rate is



32/50


*

THPSSCCscc

SCCF FFFt

KA

=

[A.30]

where KSCC = SCC model scaling factor;

= effective line age for SCC (see Section A.6)t = wall thickness;F

*

scc

SCC = SCC potential factor;

FPS = pipe susceptibility factor; and

FTH = threshold stress factor.

The core relationship involving line age and wall thickness twas inferred from the modeldeveloped for external corrosion which suggests that the failure rate is directly proportional

to line age and inversely proportional to wall thickness. Note that the line operating

temperature term in the external corrosion model was dropped because the effect of

temperature on the failure rate is implicitly covered under the broadly defined SCC potential

factor.

The SCC potential factor, FSCC, is an index that scales the rate modification factor over a

range that is intended to reflect the combined impact on the failure rate of soil environment

(i.e. soil type, drainage, topography, groundwater chemistry and pH, and temperature),

coating type and condition, and cathodic protection system effectiveness. The index

multipliers associated with each condition state are given in Table A.19.

SCC Potential of Environment FSCC

No potential 0.0

Very low potential 0.1

Low potential 0.3

Moderate potential 1.0

High potential 3.0

Very high potential 10.0

Table A.19 SCC Potential Factor

The SCC potential categories and associated indices were established so that if the soil

environment and/or the coating system is assumed to have no potential for the development

to SCC, then the SCC failure rate will be set to zero; whereas if the environment is deemed to

have a moderate potential for SCC damage then the failure rate will be equal to the baseline

rate, provided that the pipe material is susceptible and the stress level is sufficiently high.

Environments with a very high SCC potential are assumed to have failure rates one order of

magnitude higher than the reference rate.



33/50


Note that the all encompassing nature of the adopted SCC potential categories, and the order

of magnitude variations in associated indices, have been chosen to provide a way to integrate

company-specific SCC susceptibility ranking schemes into the PIRAMID model. It is

recognized that the SCC mechanism is extremely complex and dependent upon a number of

factors not explicitly addressed in the model. It is intended that operators will match their

own site susceptibility categories to the most appropriate SCC potential categories in thePIRAMID model.

The pipe susceptibility factor, FPS, is an index that is intended to acknowledge that the

microstructure and/or surface treatment of the pipe body material may render it unsusceptible

to the formation of SCC. The index multipliers associated with each condition state are

given in Table A.20.

SCC Susceptibility of Pipe FPS

Not susceptible 0.0

Unlikely to be susceptible 0.1

Likely to be susceptible 0.5

Proven to be susceptible 1.0

Table A.20 Pipe Susceptibility Factor

Intermediate susceptibility categories are provided to acknowledge that the materials

susceptibility to SCC may not be known with certainty.

The threshold stress factor,FTH, is intended to account for the impact of tensile stress on the

potential for the formation and growth of significant SCC. The tensile stress level is definedin terms of a stress ratio given by

St

DpRatioStress

2= [A.31]

where p = operating pressure (calculated from pressure profile);

D = diameter;

t = wall thickness; and

S = specified minimum yield strength.

The index multipliers associated with each adopted condition state are given in Table A.21.



34/50


Stress Ratio FTH

SR < 0.6 0.0

0.6 SR < 0.65 0.1

0.65 SR < 0.7 0.5

SR 0.7 1.0

Table A.21 Threshold Stress Factor

The threshold stress condition states and associated indices were selected based on the

assumption that the threshold stress for the initiation of significant SCC is a hoop stress level

of between 60 and 70 % of the pipe body yield strength. For hoop stress levels below 60 %

of yield, the threshold index multiplier is set to 0.0, implying that SCC failure is essentially

not possible. The uncertainty associated with the threshold stress level is reflected by index

multipliers ranging between 0.1 and 0.5 for stress levels in the transition range.

The model scale factorKSCCserves to adjust the failure rate modification factor to a value ofunity for the SCC reference sectiondefined as the line section associated with the reference

value of all line attributes that influence the SCC failure rate estimate. The intention is that

the baseline failure rate for SCC should apply directly to the reference section (hence the

need for a corresponding attribute modification factor of 1).

The expression forKSCCis obtained by first rearranging Equation [A.30] and setting AF= 1.0

to give

1*

THPSSCCscc

SCC

FFFt

K

=

[A.32]







values are considered to be representative of the SCC reference section:

Age = 20 years;

Diameter = 914 mm;

Pressure = 6895 kPa;

SCC susceptibility of environment = Moderate;

SCC susceptibility of pipe = Proven to be susceptible;

Wall thickness = 9.14 mm; and

Yield Strength (SMYS) = 448 MPa.



35/50


The corresponding model scale factor isKEC= 4.57 x10-1

.

A.5.6 Manufacturing Cracks

Pipeline failure associated with manufacturing cracks is currently restricted to the

consideration of seam weld fatigue only. Seam weld fatigue tends to occur in susceptibleseam welds (i.e. seams with significant starter defects) that are also undergoing significant

stress fluctuations due to line pressure variations and/or external loads. The factors that are

thought to affect the susceptibility of a pipeline to seam weld fatigue are primarily seam weld

type, the effective stress range and number of stress cycles. The specific line attributes used

in this model are listed in Table A.22.

Attribute NameUnits


Benefit Period of Hydrotest - Fatigue

Cracksyears



failure rate due to seam weld fatigue.

Benefit Period of Inspection - Fatigue

Cracksyears

The length of time over which an inspection and

maintenance event is assumed to provide a reduction

in the failure rate due to seam weld fatigue.



test was performed.

Date of Last Inspection - Fatigue Cracks YYYY/MM/DD


maintenance event having an effect on seam weld

fatigue was performed.


Effectiveness of Inspection - Fatigue

Cracks%

The reduction in the failure rate due to seam weld

fatigue resulting from the most recent inspection and

maintenance event.

Pressure Cycles cycles/year

The effective number of pressure cycles experienced

by the pipeline on an annual basis. (Note that complex

pressure vs. time loading histories should be

characterized by a representative single value Pressure

Range and an associated annual number of Pressure

Cycles.)

Pressure Range kPa (psi)

The effective pressure range associated with cyclic

fluctuations in line pressure during routine operation.

(Note that complex pressure vs. time loading histories

should be characterized by a representative single

value Pressure Range and an associated annual

number of Pressure Cycles.)

Seam Weld Type ChoiceA characterization of seam weld quality with respect to

fatigue resistance.


Table A.22 Line Attributes Required by Manufacturing Cracks Model



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The fatigue life of a weldment,NR, is typically expressed using a relationship of the form

[A.36]log NR( )= b m log Sr( )

where b andmare random variables that can be estimated from regression analysis of fatigue

test results, and Sr is the stress range perpendicular to the weldment axis. For longitudinalseam welds, the stress range is given by

t

DpS rr

2= [A.37]

where pr = pressure range;

D = diameter; and

t = wall thickness.

Adopting the parameter and model uncertainty characterizations developed in the Superb

project (Superb 1996) and the fatigue curve transformation model described by Albrecht

(1983), Equations [A.35], [A.36] and [A.37] can be combined and recast into the following

expression for the probability of failure for a single weld

( ) ( )

+

+

+

=

2

2

2

2

2

2

2

)log(log

cov)10log(

1cov

)10log(

1cov

)10log( Lr

rL

NSb

SbN

SWF

m

mP

[A.38]

where )log( LNu ( )LNlog ;= coefficient of variation on the load cycles = 0.18;

LNcov

)log( rSu ( )rSlog =

t

Dpr

2log ;

= coefficient of variation on the stress range = 0.10; and

= cov on the stress history approximation model = 0.30.

rScov

cov

The mean value of the number of applied load cycles is given by

*

mcLL nN = [A.39]

where nL = average annual number of pressure cycles per year; and

= effective line age for seam weld fatigue (see Section A.5.8)*mc



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The probability of fatigue failure for a given seam weld can therefore be estimated from

Equation [A.38] using the pressure cycle estimate given by Equation [A.39] if fatigue curve

parameters appropriate for the type and quality of weld are available.

Based on generally accepted probabilistic characterizations of fatigue life for standard

categories of structural welds (DnV 1984) the fatigue resistance parameters given inTable A.23 are considered representative for the various categories of seam weld quality.

Seam Weld Type Weld Classification / Descriptionb b

m

None

(seamless)B (plain steel, as rolled) 15.3697 0.1821 4.0

High quality weld

(with NDT)C (transverse butt weld w/o NDT) 14.0342 0.2041 3.5

Good quality weld

(without NDT)D (transverse butt weld w/o NDT) 12.6007 0.2095 3.0

Suspect weld F2 (one-sided butt weld w/o backing) 12.09 0.2279 3.0

Poor quality weld W (partial penetration weld) 11.5662 0.1846 3.0

Table A.23 Fatigue Resistance Parameters

Finally, to account for the fact that the model developed above considers only a single

weldment, a multiplier is required to convert the probability of failure per seam weld into a

probability of failure per unit line length (see Equation [A.33]). Assuming that the seam on

each pipe joint constitutes a distinct weldment, and assuming further an average joint length

of approximately 10 m, this implies that there are on the order of 100 distinct weldments perkilometre of pipeline, hence

[A.40]NSW = 100

A.5.7 Seismic Hazards

A.5.7.1 Overview

Pipeline failure associated with seismic hazards is currently restricted to the consideration of

failures caused by ground movement resulting from the lateral spreading of soil liquefied

during a seismic event or ground movement directly associated with fault displacement.

Seismic wave propagation, and seismically induced landslides and subsidence, are not

addressed because historical data suggests that these damage mechanisms are typically much

less likely to cause line failure than lateral spreading and fault displacement.



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Failures due to lateral spreading are associated with sections of pipeline that pass through

seismically active areas where the soils have the potential to liquefy and thereby become

unstable during significant seismic events. The model developed to quantify the

susceptibility of a pipeline to failure by lateral spreading takes into account the intensity and

duration of ground movement during a significant seismic event, the susceptibility of the

surrounding soil to liquefaction during that event, the slope of the ground, and the overallductility of the pipeline as reflected by girth weld type. The specific line attributes used in

the model are listed in Table A.24.

Failures due to fault movement are associated with sections of pipeline that intersect active

fault planes. It is assumed that companies operating pipelines

01. historical-based probability estimation for onshore pipelines

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