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A ROBUST APPROACH TO PIPELINE INTEGRITY MANAGEMENT USING DIRECT ASSESSMENT BASED ON STRUCTURAL RELIABILITY ANALYSIS

Andrew Francis, Tim Illson, M A McCallum & M McQueen Advantica Loughborough UK PH: +44 1509 282719 Fax: +44 1509 283118 Andrew.Francis@advantica.biz Abstract The basic objective of a pipeline integrity management system is to ensure that the load applied to the pipeline remains lower than the resistance to that load. This is customarily achieved by implementing measures at the start of life that ensure that a ‘safety margin’ exits at that time, and then periodically collecting information, during life, in order to ensure that the margin is not lost. Techniques that have been traditionally used for obtaining such in-service information include in-line inspection (ILI) and the hydrostatic test. These techniques have previously been favored since the interpretation of their impact on structural integrity has been perceived to be relatively straightforward. However, these approaches are not always practicable and therefore alternatives are sometimes necessary. For external corrosion, valuable information can be obtained using surface measurement techniques such as Close Interval Survey (CIS), Direct Current Voltage Gradient (DCVG) and other so-called Direct Assessment (DA) techniques. For internal corrosion, equivalent surface measurement techniques do not exist and therefore alternative sources of information are required. To this end Advantica have developed a (DA) technique based on predictive multiphase flow modeling that, combined with knowledge of the pipeline topography, can be used to determine the likely sites of water ‘hold-up’ and hence internal corrosion. However, both above ground measurement techniques and predictive modeling are subject to uncertainty and therefore do not always locate the presence of corrosion. Moreover, it is possible that the presence of corrosion may be identified erroneously. In order to account for this uncertainty, Advantica have developed a new technique, based on Structural Reliability Analysis, for robustly interpreting the


impact of results from above ground surveys and predictive modeling on the structural reliability levels. This paper describes the development and application of these techniques for the purpose of integrity management. Case studies involving both external and internal corrosion are presented which, clearly demonstrate the application, and emphasize the value of the technique as a basis for integrity management.

INTRODUCTION External Corrosion Direct Assessment (ECDA) has been defined as “a structured process that is intended to improve safety by assessing and reducing the impact of external corrosion on pipeline integrity. By identifying and addressing corrosion activity and repairing corrosion defects and remediating the cause, ECDA proactively seeks to prevent external corrosion defects from growing to a size large enough to impact on structural integrity” [1]. It is widely accepted that the process consisting of four steps. These are •

Pre-Assessment

Indirect Inspection

Direct Examination

Post Assessment

The purpose of the pre-assessment is to obtain an indication of the level of integrity that currently exists on the pipeline system. This may vary from location to location and therefore this pre-assessment can be regarded as part of a broader process that is used to identify segments and rank these in terms of risk. However, this generally involves the consideration of other causes of failure. This risk-ranking phase is beyond the scope of this paper and the process described herein is based on the assumption that the identification of pipeline segments has been undertaken. The pre-assessment is thus limited to the assessment of integrity for given segments. The approach adopted is use Structural Reliability Analysis [2-7] taking account of existing information in order to establish a prior view of the probability of failure of a given segment. Such information would include basic pipeline physical parameters such as operating pressure, material grade, wall thickness and diameter. Additionally, pipeline age and coating time would usually be known and taken into account. Other relevant information would include results of previous above ground surveys and records excavations and repairs. However, these are not always available and assumed levels of corrosion may be used based on comparisons with similar systems of a similar age. Appropriate conservatism is introduced when such assumptions are required. The results of the SRA are used as a basis for deciding on the requirements of the next three stages.


For segments for which the current knowledge of the integrity is considered to be insufficient indirect assessment is undertaken to acquire further information. This involves the use of above ground surveys such as Close Interval Survey (CIS) and Direct Current Voltage Gradient (DCVG). The purpose of the latter is detect coating damage, whilst CIS is used to detect the presence of active corrosion. An important factor associated with both of these (and other) above ground survey techniques is that they are not 100% reliable. Sometimes they fail to detect the damage, i.e. the Probability of Detection (PoD) is less than 1 and sometimes they indicate damage when damage is not present, i.e. the Probability of False Indication (PfI) is greater than zero. Direct measurements at excavation sites are used to take account of this unreliability and to improve the knowledge of defect sizes. Excavations are mainly undertaken at sites at which the surveys indicate coating damage is likely to be present. The observations made at these sites provide information for use in the post assessment. When corrosion is found at these sites, the size of the damage is used to update the prior distribution of defect depth. The discovery of coating damage and/or active corrosion maintains (but does not change) the prior belief of level of the reliability (PoD & PfI) of the surveys. When coating damage and/or active corrosion is not found at these sites then the prior value of the PfI may be changed as a result of Bayesian Updating. A small number of excavations are made at sites at which damage has not been indicated. (Note that in practice these are made at sites at which other remedial work is required, e.g. installation of test posts) When no damage is found at these sites, this maintains (but does not change) the prior belief of level of the reliability (PoD & PfI) of the surveys. When coating damage and/or active corrosion is found, the prior value of the PoD may be changed as a result of Bayesian Updating. The outcome of the above process is used in the post assessment to update the expected number of sites at which active corrosion is expected and to determine the posterior probability of failure using the updated defect size distribution. Depending on the value of the posterior failure probability, the integrity of the segment is either declared acceptable or more excavations are undertaken followed by further analysis. The above text has provided a brief outline of a rigorous process for managing the threat due to external corrosion. However, the approach may also be applied to manage the threat due to internal corrosion. Stages 1,3 and 4 apply equally to internal corrosion, but of course above ground survey techniques (stage 2) are not applicable and an alternative indirect measurement technique is therefore required. To this end hydraulic modelling has been identified as a technique for predicting the likely locations of internal corrosion damage. Based on locations of


‘low points’ inclination and length of slopes, temperature, water content and flow rate, hydraulic modeling is used to determine the positions at which water is likely to ‘drop out’ and hence promote corrosion. Data required for this purpose and indeed the modeling technique are subject to uncertainty and this is addressed in an analogous manner to that used for above ground surveys. A detailed description based on a recent case study is provided below of the use of direct assessment for managing the threats due to both external and internal corrosion. A number of segments were identified. However, in the interests of brevity the analysis of only two of these is presented here. The relevant physical details of these are given in Table 1.

PRE ASSESSMENT The pre-assessment primarily involves the use of SRA to determine an initial estimate of the probability of failure based on information that is available prior to the undertaking of any direct and indirect examinations. The initial failure probability is computed using ‘prior’ distributions and is referred to as the prior failure probability. SRA is essentially a process for combining pipeline physical properties and damage data taking, taking account of uncertainty in order to determine the failure probability. The process is described in detail in [2-7]. However, for the present publication the focus is on the inputs and outputs rather than the process itself. In addition to the expected number of internal and external corrosion defects, the parameters that determine the structural integrity are pressure, P , yield strength, σ y , ultimate strength, σ u , diameter, D , wall thickness, w , defect depth, a , and defect length, l . Details of the limit state function are given in [2-7]. Each of the parameters is subject to uncertainty that needs to be taken into account by the SRA. The data required for this purpose is generally provided by a range of different sources. However, within this publication, the focus is restricted to the parameters that are of direct relevance to the method, namely defect depth and defect length. The treatment of other parameters is discussed in [2-7]. Frequency of Occurrence of External Corrosion Defects No previously reported corrosion damage was available. Consequently, information gathered from similar systems (in the UK) was used and, based on the age of the pipeline, the prior expected number of coating defect sites per mile, EN CD , was found to be 11.88. Furthermore, information gathered from the UK Transmission system indicates that the proportion of sites with coating defects that will have active corrosion, α , is about 1%. The pipelines for which this observation were made have similar coating and are of similar age to the system under consideration and, assuming no marked difference between levels of protection, it was considered reasonable


to assume this statistic applies here. The expected number of sites with active corrosion, EN active , was thus assumed to be 0.1188 per mile. Depth of External Corrosion Defects No initial data describing the uncertainty in this external corrosion defect depth were available and therefore recourse to another data source was necessary. To this end data that have been collected over a period of in excess of 25 years from investigations of the UK Transmission system were used. A statistical analysis of these data revealed that the defect depth can be described by a Weibull distribution with a shape parameter α and a scale parameter β = K (t − t 0 ) n where t denotes the time since commissioning and t 0 denotes the time that elapsed before the defects were introduced. Values of α , K and n were found to be 2.3328, 0.0244 and 0.65 respectively. For the Weibull distribution used, the mean defect depth, µ a is given by

µ a = βΓ(1 + 1 / α ) where Γ denotes the Gamma Function. Assuming a 40-year life to date, and that t 0 = 0 , gives value for β of 0.268 and hence a mean defect depth of 0.237. Length of External Corrosion Defects The defect length is also a time dependent quantity. However, the effect of growth of this quantity is far less significant than the growth of defect depth. In general it can be assumed that the length is governed by the length of the coating defect and provided that no further loss of coating occurs the defect length can be assumed to remain constant with time. No initial data describing the uncertainty in this quantity were available for the pipeline and recourse to another data source was necessary. Using the same source as for depth, statistical analysis of the data revealed that the defect length is described by a Weibull distribution with shape parameter α = 0.8752 and scale parameter β = 5.12 inches. This gives a means value of 5.5 inches. Frequency of Occurrence of Internal Corrosion Defects Based on the number of inlet points on the pipeline and the potential range of flow rates nine potential hold-up sites were identified implying a prior incident frequency of 1.125 per mile. Depth of Internal Corrosion Defects For internal corrosion to occur, there must be liquid water present. This water can either be introduced at a point of entry or condense out of the gas due to low ambient temperatures. For the present study only the latter is considered. In the USA, gas generally contains 7lbs/mmscf giving a dew point of 27oF at 600 psi. Thus water will condense upon the pipe wall once it reaches this temperature. The number of days per year during which corrosion can occur is


considered to be equal to the number of days, TE , for which the ambient temperature falls below 27oF An analysis of NOAA data reveals that the uncertainty in TE can be represented by a Lognormal distribution with mean, µ TE , equal to 27 days and a standard deviation, σ TE , of 13 days. On the days that corrosion will occur, the corrosion growth rate, a , is related to CO2 partial pressure that is related is to the operating pressure. An analysis of partial pressure variations that occurred on the pipeline, resulted in a growth rate that can be represented by a Normal distribution with a mean, µ a , of 1.009mm/yr and a standard deviation, σ a , of 0.009. Assuming that the growth rate, although subject to uncertainty, remains constant over time, the updated growth rate is given by a=a

TE , 365

and it follows that, for given TE , the distribution of growth rate is given by p ( a | TE ) =

365  365a  p . TE a  TE 

Hence, the prior distribution of growth rate, p (a ) , is given by a

365  365a  p p (TE ) dTE TE a  TE  0

p (a) = ∫ a

The distribution of defect depth at time t (>0) is thus given by 1 p(a) = p (a / t ) . t a

After a life to date of 40 years, this results in a distribution with mean, µ , value of 2.538mm and a standard deviation, σ of 1.202mm. Length of Internal Corrosion Defects In general it can be assumed that the length is governed by the length of the hold-up and can be assumed to remain constant with time. A Lognormal distribution with mean, µ , equal to 6 inches and a coefficient of variation of 25% was considered to be an appropriate prior distribution.


Prior Failure probabilities Tables 2 and 3 show the probabilities of failure, during the year 2004, due to external and internal corrosion respectively Figures 1 and 2 show the leak, rupture and total prior failure probability due to external corrosion between 2004 and 2020. Figure 3 and 4 show the leak, rupture and total prior failure probability due to internal corrosion between 2004 and 2020. For both external and internal corrosion, based on Advantica’s experience of conducting similar studies on onshore pipelines, these prior failure probabilities are considered to be unacceptable. The information gathered from the indirect assessments, d i r e c t measurements and hydraulic modeling was therefore necessary to justify continued safe operation of these pipeline segments The following sections summarize the findings of data gathering exercises and a demonstration of the updating of the failure probabilities is given subsequently.

INDIRECT EXAMINATIONS Several above ground survey techniques were adopted including pipeline current mapper and soil resistivity measurements. However, in the interests of brevity only the effects of of CIS and DCVG are reported here. Close Interval Survey(CIS) The CIS was performed over the entire 8-mile segment. To facilitate this survey, a total of 4 current interrupters were installed. The criteria used to rank the effectiveness of the of the CP system is: Type I – ON & OFF potentials >–850mv (i.e. more positive): Probable Active Corrosion Type II – ON < -850mv, OFF > -850mv: Possible Active Corrosion Type III – ON & OFF < -850mv: Probable Inactive Corrosion The main findings from the survey, are summarized as: First Segment – Predominantly Type II indications, with the exception of a small area, where Type I conditions exist. Second Segment – Type III indications only.


Direct Current Voltage Gradient Based on the results from the correlated CIS and PCM surveys, approximately 4 miles were surveyed using DCVG. The survey produced 189 indications, summarized as: • 5 (indications) >35%IR • 56 15 – 35%IR • 128 <15%IR

Hydraulic Modelling An internally developed pipeline simulation program called Netflo was used for hydraulic modelling. The modeling addressed the condensation of water from nominally dry gas and the transportation of wet gas from well inlets. Netflo uses values of physical and inlet parameters to predict flow patterns and water accumulation. The following pipeline physical parameters were used : • • •

Pipe diameter – 14 inches Pipe internal roughness – 0.0024 inches Pipe wall thickness – 0.25 inches

The pipeline inlet parameters were: • • • • •

Pressure – 600 psig Temperature – 65oF Low flow rate – 17 mmscfd Normal flow rate – 31 mmscfd High flow rate – 60 mmscfd

The topography of the pipeline was derived from a GPS survey. Essentially, the GPS co-ordinates and elevation were converted into a topographic profile for use within Netflo. Heat transfer coefficients were derived from the burial depth of the pipeline using the equation:

hsoil =

Where:

k soil D  2H  cosh −1   2  D 

hsoil = heat transfer coefficient due to burial


Ksoil = thermal conductivity of soil D = outside diameter of buried pipe H = distance between top of soil and centre of pipe A thermal conductivity of 0.75 W/mK was used for the soil. This would be typical of moist clay. A winter ambient air temperature of 43oF was used for the modeling to reflect a severe case for water condensation. The hydraulic modelling indicated that there were numerous locations within the pipeline segment where the condensed water from nominally dry gas could accumulate at the flow rates used. From an internal corrosion perspective the most important accumulation sites are those closest to the inlets and these were identified. The two pipeline segments contains a number of tap points where potentially wet gas from wells entered the line. The hydraulic modelling thus identified the first accumulation points downstream of well inlets.

DIRECT EXAMINATIONS ECDA ECDA From an assessment of the results from stage 2, the severities of the indications were classified in order to prioritize which indications should be excavated for further analysis. The indications can be summarized as follows: • 26 Anomalies - Type II & Minor • 102 Anomalies - Type III & Minor • 9 Anomalies - Type II & Moderate • 47 Anomalies - Type III & Moderate • 5 Anomalies - Type III & Severe A total of 9 sites were selected for direct examination. An additional 5 excavations were also performed at locations where there were no indications of coating anomalies from the above ground surveys. This was carried out to determine both the accuracy and reliability of the survey techniques. ICDA A number of sites (see Table 4) were selected for excavation, based on the results of the hydraulic modelling. Inspection at each of these sites was undertaken using a guided wave ultrasonic tool (GUL). No significant internal corrosion was found at any of the excavation sites

POST ASSESSMENT


Updating Expected Number of Coating Defects Sites For DCVG, prior values of the probability of detection and probability of false indication were assumed to be 0.9 and 0.1, respectively. The number of DCVG indications, N DCVG , found was 204. Following the survey, 9 excavations were undertaken at sites where the DCVG survey indicated coating defects and 5 excavations were undertaken at sites where the DCVG survey did not indicate coating defects. The methodology described in [8] was used with this information to update the probability of detection, the probability of false indications and subsequently the expected number of coating damage sites. Coating damage was found at each of the 9 sites at which damage was expected; based on Bayesian updating, this observation reduced the value of PfI from 0.1 to 0.082. No coating defects were found at the 5 sites at which damage was not expected; based on Bayesian updating, this observation increased the value of the PoD from 0.9 to 0.91 Based on the above value of N DCVG and the updated values of PfI and PoD, the expected number of coating damage sites per mile increased from 11.88 to 18.78.

Updating Expected Number of Active External Corrosion Sites, Assuming 1% that active corrosion is present at 1% of the sites at which coating damage is present, the expected frequency of occurrence of sites having active corrosion is 0.1878 per mile. For CIS, prior values of the probability of detection and probability of false indication were assumed to be 0.88 and 0.1, respectively Since there were no active corrosion sites indicated, the probability of false indication cannot be updated. No active corrosion was found at any of the 14 excavation sites at which active corrosion was not expected; base on Bayesian updating, this observation increased the probability of detection from 0.88 to 0.89. Using this outcome, the expected number of active corrosion sites per mile changes from 0.1878 to 0.176.

Updating External Corrosion Defect Depth Distribution The measurements of defect depth size made at the sites of bell-hole excavations, allows an updating of the defect depth distribution p (a, T ) to be undertaken, where T is the time of the excavation relative to some reference time. Using Bayesian updating techniques, this resulted in an expected value of β of 0.0020 inches, compared to a prior value of 0.268 inches.


It is immediately apparent that the updating has a significant effect on the prior distribution. The mean value of the prior distribution is 0.237 inches and the mean value of the updated distribution is 0.0018 inches. This highlights the conservatism of the initial assumption. It should be noted that the mean value of the observed data is 0.0016 inches. It can readily be deduced that if one further excavation were to be undertaken then it would need to have a depth in excess of 2.4 inches in order to increase the observed mean to the prior value of the mean. Based on the current distribution, such a defect is incredible. On the contrary more excavations will reduce the mean value still further, since this distribution is slightly more onerous than the observed data. It thus follows that provided acceptable failure probabilities are obtained based on the existing distribution, no further excavations are necessary.

Updating External Corrosion Defect Length Distribution The measurements of defect length size at the sites of bell-hole excavations, allows an updating of the defect length distribution. Using Bayesian updating techniques, this resulted in an expected value of β of 0.77 inches, compared to a prior value of 5.12 inches. It is immediately apparent that the updating has a significant effect on the prior distribution. The mean value of the prior distribution is 5.5 inches and the mean value of the updated distribution is 0.82 inches. This highlights the conservatism of the initial assumption. It should also be noted that the mean value of the observed data is 0.56 inches. It can be readily deduced that if one further excavation were to be undertaken then it would need to have a length in excess of 54 inches in order to increase the observed mean to the prior mean. Based on the current distribution the likelihood of such a defect is incredible. On the contrary more excavations are likely to reduce the mean value of the updated distribution, since this is more onerous than the observed data. It thus follows that provided acceptable failure probabilities are obtained based on the existing prior, no further excavations are necessary.

Updating Internal Corrosion Defect Depth Distribution The measurements of defect depth size for internal indications at the calibration dig sites, allows an updating of the distribution of days on which the temperature is below 27oF. Using Bayes Theorem, the posterior distribution of TE can be obtained using p (TE | a ob ) =

p (a ob | TE ) p (TE ) ∞

∫ p(a 0

ob

| TE ) p (TE ) dTE


where the prior distribution p (TE ) represented is by a Lognormal distribution with σ TE , of 13 days (see mean, µ TE , equal to 27 days and a standard deviation, above). Using the results of the calibration digs, resulted in an updated mean value µ TE of 1.39 days. This information allows us to update our view on the defect depth distribution. The updated distribution is Lognormal with mean, µ , equal to 0.126mm and a standard deviation, σ , equal to 0.002mm. These compare with prior values of 2.538mm and 1.202mm, respectively.

Updating Internal Corrosion Defect Length Distribution Using the results of the excavations, this gives an expected value of µ of 0.49 inches, compared to a prior value of 6 inches

Updated Probability of Failure SRA was used to determine the probabilities of failure based on the updated distributions. The updated failure probabilities in the year 2004 for external corrosion are shown in Table 5. When compared with the prior failure probabilities in Table 2, it is immediately obvious that using the information gathered from the above ground surveys and the excavations, the probability of failure due to external corrosion is reduced to negligible values. Immediately following updating it is thus appropriate to state that the failure due to external corrosion in 2004 is incredible. Figures 5 and 6 show the effect that the updating has on the probability of failure due to external corrosion in the period from 2004 to 2020. The marked improvement for ‘earlier years is clearly visible. Furthermore, it is seen that the total probability of failure due to external corrosion remains acceptably low until around 2015. The implications of this outcome are that it is not strictly necessary to undertake a further assessment for a period of about 10 years. Moreover, if the probability of a rupture alone is considered, (more severe consequences) it is noted that the probability remains acceptable for the whole of the time period considered. When considering the above outcome, it is worth noting that if a hydrostatic test or an in-line inspection are the adopted mitigation measures, CFR Parts 192 & 195 requires these to be undertaken every 5 years unless a reliable engineering justification can be made to extend this period. Based on the above the ECDA methodology has demonstrated that the overall probability of failure due to external corrosion remains negligible for around 11 years and more significantly that the probability of a rupture occurring remains


acceptable low until after 2020. The implications of this outcome are that it would be prudent to undertake a further assessment in about 11 years time. As an initial â&#x20AC;&#x2DC;benchmarkâ&#x20AC;&#x2122;, it is worth noting that if hydrostatic or in-line inspection are the adopted mitigation measures, CFR Parts 192 & 195 requires these to be undertaken every 5 years unless a reliable engineering justification can be made to extend this period. The updated failure probabilities in the year 2004 for internal corrosion are shown in Table 6. When compared with the prior failure probabilities in Table 3, it is immediately obvious that using the information gathered from the indirect examination and the excavations, the probability of failure due to internal corrosion is reduced to negligible values. Immediately following updating it is thus appropriate to state that the failure due to internal corrosion in 2004 is incredible. When the updated failure probability for internal corrosion is calculated in the time period 2004 to 2020 it is found that using the ICDA methodology, the likelihood of failure is incredible.

CONCLUSIONS A rigorous methodology for determining the integrity of pipeline systems using External and Internal Corrosion Direct Assessment techniques based on Structural Reliability Analysis and Bayesian Updating has been described. The application of the technique to a North American pipeline system has been described in detail. External Corrosion The results of the pre-assessment showed that the prior failure probabilities were unacceptable and identified a requirement for a number of above ground surveys to be conducted during the indirect Inspection stage, including, Pipeline Current Mapper, Close Interval Survey and Direct Current Voltage Gradient. Based on a consideration of the results of the indirect inspection stage, 9 sites were identified for excavations during the direct examination stage. During the direct examination stage no locations of active corrosion were detected. The results obtained from indirect inspections and direct examination were used to update the prior failure probabilities. The updated probabilities were found to be significantly lower than the prior probabilities. Based on a consideration of the results it was concluded that no further excavations were necessary and that the ECDA study would be necessary for at least a further 11 years. Internal Corrosion


The results of the pre-assessment showed that the prior failure probabilities were unacceptable and identified a requirement for Advantica to use the NetFlo software to highlight excavation sites. During the indirect inspection stage, a total of 9 hold-ups were indicated. During the direct examination stage, no locations of active internal corrosion or inactive internal corrosion were detected. The results obtained from the indirect inspections and direct examination were used to update the prior failure probabilities. The updated probabilities were found to be significantly lower than the prior probabilities and indicated that the likelihood of failure due to internal corrosion is incredible. The objective of the ICDA study was to assure the integrity of the pipeline by determining sites where internal corrosion could occur, inspecting these areas and using the results to assess whether internal corrosion was a credible threat to pipeline integrity. No significant internal corrosion was discovered in any of the sites inspected. The ICDA concept is that inspection at the sites where water would first accumulate gives implies information about the rest of the pipeline. If these sites have not corroded then other locations that have a lower probability of accumulating water should also be free of corrosion. Therefore, the lack of corrosion in the sites inspected implies that the pipeline should be essentially free of internal corrosion that would threaten its integrity. The secondary implication is that the pipeline inlet gas has been effectively dry over the history of the pipeline. If wet gas had entered the pipeline then corrosion would have been found at some of the excavation sites.


REFERENCES 1. NACE Recommended Practice RP0502-2002, Pipeline External Corrosion Direct Assessment. 2. Francis, A., Edwards, A.M., Espiner, R.J., & Senior, G., “Applying Structural Reliability Methods to Ageing Pipelines”, Paper C571/011/99, IMechE Conference on Ageing Pipelines, Newcastle, UK, October 1999 3. Francis, A, Edwards, A.M. & Espiner, R.J., “A Fundamental Consideration of the Deterioration Processes Affecting Offshore Pipelines using Structural Reliability Analysis”, Paper OMAE00-5042, ETCE/OMAE 2000 Joint Conference, New Orleans, USA, February 2000 4. Edwards, A.M., “The application of Structural Reliability Analysis Towards Developing Pipeline Integrity Management Programs”, AGA Operations Conference, May 7-9, 2000, Denver Colorado 5. Francis, A., Edwards, A.M., Espiner, R.J., & Senior, G., “An Assessment Procedure to Justify Operation of Gas Transmission Pipelines at Design Factors up to 0.8”, Paper PIPE90, Pipeline Technology Conference, Brugge, Belgium, May 2000. 6. Francis, A., Espiner, R.J., Edwards, A.M. & Hay, R.J., ‘A Consideration of Data Requirements for Structural Reliability Based Assessments of Onshore Pipelines’ 5th International Conference on Engineering Structural Integrity Assessment, Churchill College, Cambridge, UK September 2000 7. Francis, A., McCallum, M., Gardiner, M. & Michie, R., ‘A Fundamental Investigation of the Effects of The Hydrostatic Pressure Test on the Structural Integrity of Pipelines using Structural Reliability Analysis’, 20th International Conference on Offshore Mechanics and Artic Engineering, Rio de Janeiro, Brazil, June 2001. 8. Francis, A., Gardiner, M., Goodfellow, A., McCallum, M, Senior, G. & Greenwood, B, ‘A Systematic Risk and Reliability-Based Approach to Integrity Management of Piggable and Non-Piggable Pipelines’, Pipeline Integrity and Safety Conference, Houston, Texas, September 2001.’


TABLES Length(miles) Size Wall MAOP Grade Cl Segment 3 14.000 0.250 855 X46 2 1 5 14.000 0.312 855 X52 2 2

Table 1: Segmentation of the Pipeline Segment 1 2

Prior Failure Probabilities @2004 Leak Rupture Total 2.72E-03 6.20E-04 3.34E-03 2.15E-03 1.57E-04 2.31E-03

Table 2: Prior Probability of Failure in 2004 due to External Corrosion Segment 1 2

Failure Probability at 2004 Leak Rupture Total 2.29E-03 5.95E-04 2.88E-03 3.78E-04 1.88E-07 3.78E-04

Table 3: Prior Probability of Failure in 2004 due to External Corrosion Site 1

Reason 1st water hold up point from main inlet 1st water hold up point from main inlet at low flow 2nd water hold up point after main inlet 1st water hold up point after well inlet 1st water hold up point after well inlet

2 3 4 5

Result No Corrosion No Corrosion No Corrosion No Corrosion No Corrosion

Table 4: Sites selected for excavation and inspection Segment 1 2

Failure Probability in 2004 Leak Rupture Total <1.00E-10 <1.00E-10 <1.00E-10 <1.00E-10 <1.00E-10 <1.00E-10

Table 5: Updated Probability of Failure in 2004 due to External Corrosion


Segment 1 2

Failure Probability at 2004 Leak Rupture Total <1.00E-10 <1.00E-10 <1.00E-10 <1.00E-10 <1.00E-10 <1.00E-10

Table 6: Updated Probability of Failure in 2004 due to Internal Corrosion


Segment 1 Prior External Corrosion Failure Probability 1.00E+00

Probability

1.00E-01 Leak 1.00E-02

Rupture Total

1.00E-03 1.00E-04 2004

2009

2014

2019

Year

Figure 1 : Segment 1 Prior External Corrosion Failure Probability Segment 2 Prior External Corrosion Failure Probability 1.00E+00

Probability

1.00E-01 Leak 1.00E-02

Rupture Total

1.00E-03 1.00E-04 2004

2009

2014

2019

Year

Figure 2 : Segment 2 Prior External Corrosion Failure Probability


Segment 1 Prior Internal Corrosion Failure Probability 1.00E+00

Probability

1.00E-01 Leak 1.00E-02

Rupture Total

1.00E-03 1.00E-04 2004

2009

2014

2019

Year

Figure 3 : Segment 1 Prior Internal Corrosion Failure Probability Segment 2 Prior Internal Corrosion Failure Probability 1.00E+00 1.00E-01

Probability

1.00E-02 Leak

1.00E-03

Rupture

1.00E-04

Total

1.00E-05 1.00E-06 1.00E-07 2004

2009

2014

2019

Year

Figure 4 : Segment 2 Prior Internal Corrosion Failure Probability


Effect on Total Failure Probability After Direct Assessment

Probability

1.00E+00 1.00E-02 1.00E-04

Prior

1.00E-06

After Excavations

1.00E-08 1.00E-10 2004

2009

2014

2019

Year

Effect on Leak Failure Probability After Direct Assessment

Probability

1.00E+00 1.00E-02 1.00E-04

Prior

1.00E-06

After Excavations

1.00E-08 1.00E-10 2004

2009

2014

2019

Year

Effect on Rupture Failure Probability After Direct Assessment

Probability

1.00E+00 1.00E-02 1.00E-04

Prior

1.00E-06

After Excavations

1.00E-08 1.00E-10 2004

2009

2014

2019

Year

Figure 5: Segment 1 Updated External Corrosion Failure Probability


Effect on Total Failure Probability After Direct Assessment

Probability

1.00E+00 1.00E-02 1.00E-04

Prior

1.00E-06

After Excavations

1.00E-08 1.00E-10 2004

2009

2014

2019

Year

Effect on Leak Failure Probability After Direct Assessment

Probability

1.00E+00 1.00E-02 1.00E-04

Prior

1.00E-06

After Excavations

1.00E-08 1.00E-10 2004

2009

2014

2019

Year

Effect on Rupture Failure Probability After Direct Assessment

Probability

1.00E+00 1.00E-02 1.00E-04

Prior

1.00E-06

After Excavations

1.00E-08 1.00E-10 2004

2009

2014

2019

Year

Figure 6: Segment 2 Updated External Corrosion Failure Probability


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