Final_Paper

Presented at the Pipeline Pigging, Integrity Assessment & Repair Conference,Amsterdam, October 2002

Copyright © 2002 Advantica Technologies Ltd. All rights reserved.Page 1 of 14

THE USE OF STRUCTURAL RELIABILITY ANALYSIS FORMANAGING THE INTEGRITY OF HIGH PRESSURE

PIPELINESAndrew Francis & Marcus McCallum

Advantica Technologies LtdLoughborough

LE11 3GRUK

+44 (0)1509 [email protected]

ABSTRACT

The integrity of high-pressure pipelines is customarily managed by periodicallyundertaking specified inspection and maintenance activities. However, the futurelevel of integrity that will be achieved by these activities is generally unknown.Moreover, in certain cases the level of integrity that was achieved in the past is alsounknown. Clearly, the future of the pipeline is dependent on it’s past and theinspection and maintenance regime required for one pipeline may be very differentfrom that required for another, even though the nominal design parameters are thesame.

This paper describes a technique based on structural reliability analysis fordetermining the reliability of a pipeline based on a combination of limited historicalinformation and limited recent above ground survey and excavation results. It isshown how the method can be used as a basis for future inspection andmaintenance programs.

INTRODUCTIONIt is generally acknowledged by pipeline designers and operators that many factorscontribute to the overall integrity and hence safety of a pipeline. However, therelative contribution of each factor to the overall structural reliability is generallyunknown. Basically, each activity is routinely undertaken in the belief that it isnecessary and makes some contribution to the integrity but the actual worth of theactivity is not known. Also varying levels of uncertainty can be associated with eachfactor and these generally depend on the knowledge of the history of the pipeline.For instance, the uncertainty associated with a pipeline that has been in the custodyof one operator since commissioning and that has been subjected to a rigorousinspection and maintenance regime is likely to be lower than that for a pipeline thathas changed hands at least once, and that has been operated in a more relaxedmanner. It naturally follows a pipeline falling in to the latter category may requiremore extensive future inspection and maintenance than a pipeline falling into theother.



This paper describes a method based on Structural Reliability Analysis (SRA) fordetermining the reliability level for which limited initial information is available andthen for updating the reliability level based on the acquisition of further information.

A means of using this information as a basis for a future integrity managementprogramme is described.

STRUCTURAL RELIABILITY ANALYSIS

Structural reliability analysis (SRA) is a structured methodology for determining theprobability of a structure failing based on a combination of structural mechanics anduncertainty analysis. SRA comprises of six elements:

• Establishment of Limit States

• Identification of Failure Modes

• Formulation of Limit State Functions

• Uncertainty Analysis

• Evaluation of Failure Probability

• Assessment of Results

Detailed description of the overall methodology as applied to pipelines can be foundin [1-10]

APPLICATION OF STRUCTURAL RELIABILTY ANALYSIS TO AGEINGPIPELINESIn principle it is possible to use SRA to justify operational and design decisions atany stage in the life of a pipeline. For instance, at the design stage, the techniquecould be used to determine the wall thickness that would be necessary to achieve agiven reliability level [8]. On the other hand, SRA can be used to justify extending theoperational life [9] or increasing the operating pressure (uprating), of an in-servicepipeline [1 & 7].

The basic SRA procedure is the same, regardless of the application. However, thedetail can be significantly different since differing amounts of information may beavailable. For instance, at the design stage, before the pipeline exists, the designercan determine what information he would need to achieve a given reliability level andthen set out to obtain this information. This may require certain standards from thepipemill, a specified hydrostatic test pressure, and a specified inspection andmaintenance program. On the other hand, for an existing in-service pipeline there isless freedom of choice. The physical dimensions of the pipeline will clearly havealready been determined but additionally the pipeline will also have deteriorated. Thenature of this deterioration will depend on the effectiveness of the protectivemeasures and the inspection and maintenance regime that has been in place. Thechoice available to the operator is thus much reduced since few parameters willremain under his control. For the remaining life of the pipeline, these will essentiallybe limited by the operating pressure, inspection and surveillance frequencies andrepair criteria. Deciding on acceptable values for these parameters is furthercomplicated if knowledge of the history is limited or unknown.



This paper describes an approach using SRA that can be used for the purpose ofmaking operational decisions in situations where the knowledge of the history of anexisting ‘older’ pipeline is limited or unknown.

OUTLINE OF THE APPROACHThe general SRA approach hinges on combining relevant elements of uncertainty inorder to determine the probability of a failure occurring in the future. SRA can beapplied at any time during the life of a pipeline to predict the probability of a failureoccurring during the remaining life, taking account of the previous operation.

In general, more uncertainty will result in a higher predicted value of the probability offailure. It thus follows that the predicted probability of failure of a pipeline with anunknown history will be greater than that of a pipeline of a similar age for which moreinformation exists. Consequently, a more extensive future data gathering exercisemay be necessary for the pipeline having the more uncertain history. Intuitively, thiswould be expected and the SRA approach thus provides a rational consistent basisfor making a decision regarding the future operation of the pipeline.

If the pipeline has been in the custody of an operator who has systematicallymaintained a comprehensive data records management system then the availabledata may be considerable and it may be possible to reduce future data acquisitionrequirements and still maintain an acceptable probability of failure. For instance theinspection frequency may be reduced. On the other hand, if the pipeline hasundergone change of ownership, records may be sparse and it may be necessary toimplement a rigorous inspection and maintenance regime, at least in the short term.The extent and nature of the relaxation or increased rigour is determined by the SRAstudy.

The approach can be applied to address issues associated with any relevant failuremode at any time during the life of a pipeline. However, for the purpose of illustrationthis note focuses on the treatment of external corrosion issues for an ageing pipelinefor which limited historical information is available.

External corrosion is a deterioration process that leads to progressive localised lossof wall thickness and can eventually lead to breach of the pipeline wall, withsubsequent loss of containment.

In an attempt to prevent such a loss occurring, pipelines are commonly given aprotective outer coating and are provided with a cathodic protection (CP) system toprevent corrosion from occurring if localised breaches of the coating occur. Althoughgenerally infrequent, failures of both of these protective measures do occur atlocalised sites thereby allowing localised external corrosion to occur. The keyuncertainties associated with external corrosion are the likely number of sites atwhich the protective measures will have failed, and the likely sizes to which theensuing corrosion defects will have grown in a given time.

DATA SOURCES



Techniques used to provide insight into the number and sizes of defects includeAbove Ground Surveys, In-line inspections and hydrostatic pressure testing. A briefdescription of these is given below.

Above Ground Surveys

Above ground survey techniques such a Close Interval Potential Surveys (CIPS),Direct Current Voltage Gradient (DCVG) measurements and Pearson surveys areundertaken periodically to try and identify sites at which both a breach of coating hasoccurred and the CP system is not giving adequate protection. For sites that havebeen identified as potentially problematical by one or more of the surveys,excavations may be undertaken to expose the pipeline wall. If a defect is found thathas dimensions that exceed some specified critical values, a repair is undertaken.Otherwise a repair to coating alone is undertaken if necessary. (Note on someoccasions there may not even be coating damage since some indications are false;this is discussed in more detail below).

In-line inspections

In-line inspections can be undertaken by passing an inspection vehicle down thepipeline. The vehicle is driven by the flow of the product and is used to detect thepresence of pipewall metal loss often using magnetic flux leakage technique. This isa more direct and usually more reliable method than the above ground surveytechniques. However, the pipeline has to be fitted with ‘launchers’ and ‘receivers’and must be free from features that could obstruct the passage of the tool such astight bends. Localised excavations may be necessary to repair damage.

In-service hydrostatic test

An in-service hydrostatic test can be used to detect the’ absence’ of problematicaldefects. The philosophy is that if no failures occur at the test pressure (usually higherthat the operating pressure) then no failures can occur within some estimated futuretime period since any defects that were present or occur subsequently will take timeto grow. This test is not normally an attractive option for a number of reasons, notleast of these being the requirement to supply and dispose of large quantities ofwater and also the possibility of causing significant damage during the test.

INITIAL PREDICTION OF FAILURE PROBABILITY

It is assumed here that the pipeline has been operating for a number of years (>20say) and that the operator needs to decide what future corrosion managementsystems need to be in place in order to achieve an acceptable ongoing probability offailure due to external corrosion in the future. (Note this forms part of the overallintegrity management system that addresses all failure modes.)

The probability of failure due to corrosion depends on number of basic factors,including operating pressure, diameter, material grade and wall thickness.



Basic data such as nominal values of diameter, wall thickness, material grade arecommonly, but not always, available. However, the availability of information fromwhich to quantify the uncertainty in these quantities such as mill certificates may ormay not be available. If such information is available then probability densityfunctions describing the uncertainty can be readily constructed using the approachoutlined above. If the information is not available then the uncertainty can beestimated using information that is available for similar pipelines.

However, more significantly, the probability of failure due to corrosion depends thelikely number of corrosion sites and the likely sizes of defects that are present at agiven time in the future.

For a system that has been subjected to a rigorous inspection and maintenanceregime and for which extensive records of CIS, DCVG, in-line inspection and repairsexist, probability density functions can be readily constructed and the future failureprobability can be determined. If the pipeline has been operated under such aregime it is likely that any problems will have been remedied. It is therefore possiblethat the probability of failure could be maintained at an acceptable level even ifcertain activities were relaxed.

On the other hand if the pipeline has been operated under a ‘more relaxed regime’this does not mean that the pipeline cannot be operated safely in the future.However, it does mean that the initial calculated probability of failure is likely to behigher, since it will be based on more uncertain information, and therefore a morerigorous data acquisition may be necessary in the future, in order to update theprobability of failure.

Assuming that limited data are available then conservative estimates of the likelynumber of defects and sizes will have to be made based on information available forother similar pipelines. Because of the conservative nature of these estimates theinitial probability of failure is likely to be unacceptable and updating of this quantitymay be necessary based on the collection and use of further data.

Procedures for doing this are described below using above ground survey resultsand excavations.

UPDATED PROBABILITY OF FAILURE

In order to update the calculated probability of failure it is necessary to update thedistributions that describe the uncertainty in the key parameters. For corrosion theseare the number and sizes of defects. Procedures for updating these quantities areoutlined below. A detailed description of the method is given in [10].

Updating the estimate of the number of defects

The number of defects that may be present is subject to uncertainty and thereforeshould be described by a probability density function.



It is assumed here that the initial distribution )( ACNp can be constructed based onavailable information for the pipeline (or similar pipelines), where ACN denotes theactual number of defects. Because this distribution is based on limited and/orassumed data it will be subject to uncertainty.

Results from above ground surveys can be used to improve the distribution. Aboveground survey techniques will indicate that AGSN defects are present.

Typical results for CIS and DCVG surveys are shown in figures 1 and 2. Thesefigures illustrate schematically how the data are interpreted.

In general AGSN will differ from ACN because the survey techniques are also subjectto uncertainty. The techniques will not detect all defects, i.e. the probability ofdetection PoD is less than unity. The techniques will sometimes indicate that a defectis present when there is no defect, i.e. the probability of a ‘false indication’, PfI isgreater than zero. The values of PoDand PfI depend on the technique, theconditions under which it is used and the user. However, in general a lower value ofPoD will mean that AGSN is an underestimate of ACN and a higher value of PfI willmean that AGSN is an over-estimate of ACN .

Conditional probability theory (sometimes called Bayesian updating) is used todetermine the probability )|( AGSAC NNp that there are ACN defects present given thatthe above ground survey technique indicated, AGSN . A precise expression forperforming the updating based on conditional probability, having the functional form

))(,,()|( ACAGSAC NpPfIPoDFNNp =

is used. The quantity on the left hand side of the above expression is referred to asan updated version of )( ACNp . Note that updating can be applied successively ifmore than one type of above ground survey is undertaken.

Updating the defect size distribution

It is assumed here that the initial distribution ),( 0tap can be constructed based onavailable information for the pipeline (or similar pipelines), where a denotes thedefect depth and 0t is the current age of the pipeline. Because this distribution isbased on limited and/or assumed data it will be subject to uncertainty.

Results from sample bell-hole excavations can be used to update the distributions.

The defects found during M excavations can be placed into n categories, e.g.

(Category 1) nwa /0 << ,(Category 2) nwanw /2/ << ,

…,



(Category i) niwanwi //)1( <<−…,

(Category n) wanwn <<− /)1(

wherew is the wall thickness. In general im defects will be placed in each categorywhere

Mmn

i =∑1

.

The updated distribution can be obtained using conditional probability to determinethe distribution of defect sizes given the observations made during the excavations.The expression for updating takes the functional form,

)),(,()1,|,( 00 tapmFntoimtap ii ==

where the function is derived from the likelihood of the observations being made.

The updating will change the shape of the distribution in accordance with theobservations. For instance if a number of defects have been found and they all havevery similar depths and all of these are greater than the current mean depth, then theupdating leads to an increase in the current mean value but possibly to a decrease inthe standard deviation because of the lack of spread in the results. On the otherhand if there is significant spread in the observations but the mean value is close tothe mean value of the current distribution then the updating will result in little changeto the mean but may increase the standard deviation.

A similar approach applies to defect length.

The effect of time

The distribution of defect depth determined by the approach given above willdescribe the uncertainty in depth at time, 0t . Clearly as time increases into the futurethe defects may grow. The distribution of defects at some time 0tt > can bedetermined taking account of a corrosion growth law that is also subject touncertainty.

Evaluation of failure probability

Having determined the important distributions the time dependent probability offailure can be evaluated using the SRA technique. The computed value is used asbasis to decide on the level of future mitigation that will be required in order tomaintain an acceptable level of structural integrity.



CASE STUDYThis study demonstrates how the CIPS, DCVG survey and Bell-Hole excavationresults are used to update the failure probability by updating the distributions ofnumber of defects and defects and how the results can be used as a basis for futureintegrity management

The study considers a 100km long, high pressure, 24” transmission pipeline that wascommissioned in 1980. Knowledge of the history of the pipeline is limited although itis known that the line has not previously been in-line inspected. However, recentCIS, DCVG and excavation results are available.

Updating the defect distribution

The line has been surveyed in-service using the CIPS technique, followed by aDCVG survey and finally by a series of Bell-Hole excavations. The most recentsurveys were undertaken 20 years after commissioning.

The PfI and PoD values had been established previously by correlating CIPS andDCVG data with in-line inspection results from a ‘similar’ piggable pipeline. For theCIPS system it was found that 1.0=PfI and that 75.0=PoD . The correspondingvalues for the DCVG survey were 05.0=PfI and .85.0=PoD

Defect distributions after CIPS and DCVGBased on considerations of the age of the pipeline and previous CIPS, DCVG andBell-Hole excavations that the prior distribution of the number of defects in the entirelength of the line, )( ACNp , is given by

)102,5.11,()( === βαACAC NNp Weibull .

Hence the expected value of ACN is 98; see Figure 3. This prior distribution isupdated using the most recent CIPS and DCVG data using the approach outlinedabove and described in detail in [10].

The CIPS has indicated that there are 75 indications. The updated distribution,)|( CIPSAC NNp based on these indications, is shown in Figure 3; the expected

number of defects as 91.

The DCVG survey is also applied to the entire length of the pipe and this gives 60indications. The updated distribution )|( DCVGAC NNp gives the expected number of74. The new distribution following both CIS and DCVG is shown in Figure 3.

Defect distributions after Bell-Hole ExcavationsTwenty excavations were undertaken at sites at which defects were indicated by thesurveys and 6 excavations are undertaken at sites at which no defects were



indicated. Nineteen defects were found at likely defect sites and 0 defects werefound at unlikely defect sites.

The updated values for PoD and PfI are shown in Table 1, with the old valuesshown in the brackets. It is seen that only marginal changes were made to thesevalues based on the observations.

CIS DCVGProbability of Detection )(PoD 0.81 (0.75) 0.87 (0.85)

Probability of False Indication )(PfI 0.09 (0.1) 0.05 (0.05)Table 1 : Change in PoD and PfI after Excavations

This resulted in an updated distribution for the number of defects shown in Figure 3,with an expected number of defects marginally reduced from 74 to 72.

Updating the Failure Probability

The effect on the failure probability using the updated distribution for the number ofdefects is shown in Figure 4. In this case the results show that the CIPS, DCVG andexcavation information has only a marginal improvement on the failure probability.

Updating the Defect Growth law

The initial growth rate is assumed to be 0.2mm/yr; during the Bell-Hole excavations,based on previous experience of ‘similar’ pipelines.

The Bell-Hole excavations were performed after 20 years of the pipeline operation.The range of sizes of the 19 defects that were found is shown in Figure 5. Usingthese values to update the distribution of defects resulted in a reduction in theaverage growth rate from 0.2mm/yr to 0.14mm/yr. This reduction is predictedbecause the sizes of the defects that were found were generally lower than predictedby the original growth rate.

The effect of the reduction on the probability of failure is illustrated in the nextsection.

Updating the Failure Probability

Figure 6 shows the (original) calculated failure probability associated with a constantdefect growth rate (K=0.2mm/yr) applied for a 60year period. The updated failureprobability is obtained by applying the K=0.2mm/yr for the first 20 years followed bythe updated value, K = 0.14mm/yr, for the remainder of the 60 year period.

It can be seen that the improvement in the confidence in the integrity of the pipelinebased on the excavation results is significant. Prior to the excavation there was apredicted steep increase in the probability of failure at about the year 2020.Following excavation the steep increase was delayed for about 15 years.

The overall outcome of this analysis is to inform the operator that at the momentthere is no need for concern regarding corrosion. However, it would be prudent tocontinue to undertake CIS/DCVG surveys in alignment with current companypractice in the near future in order to maintain this level of confidence.



Of course, had more onerous defects been discovered than those that were initiallypredicted, then an increase in the growth rate would have ensued and it may havebeen necessary to embark on a more rigorous surveillance and maintenancescheme.

CONCLUSIONSA rigorous methodology for determining the level of integrity of an onshore pipelinebased on structural reliability and Bayesian statistics has been presented.

It has been shown how the methodology takes account of CIPS, DCVG and Bell-hole excavation results in order to update the confidence in the predicted probabilityof failure due to external corrosion.

A simple case study has illustrated how significant benefits can be derived from arelatively small number of bell-hole excavations

REFERENCES

[1] Francis, A., Edwards, A.M., Espiner, R.J. & Senior, G., ”An AssessmentProcedure to Justify Operation of Gas Transmission Pipelines at Design Factorsup to 0.8”, Paper PIPE90, Pipeline Technology Conference, Brugge, Belgium,May 2000.

[2] Francis, A., Edwards, A.M., Espiner, R.J. & Senior, G., “Applying StructuralReliability Methods to Ageing Pipelines”, Paper C571/011/99, IMechEConference on Ageing Pipelines, Newcastle, UK, October 1999.

[3] Francis, A., Edwards, A.M. & Espiner, R.J., “A Fundamental Consideration of theDeterioration Processes Affecting Offshore Pipelines using Structural ReliabilityAnalysis”, Paper OMAE00-5042, ETCE/OMAE 2000 Joint Conference, NewOrleans, USA, February 2000.

[4] Edwards, A.M., “The application of Structural Reliability Analysis TowardsDeveloping Pipeline Integrity Management Programs”, AGA OperationsConference, May 7-9, 2000, Denver Colorado.

[5] Francis, A., Espiner, R.J., Edwards, A.M. & Hay, R.J., ”A Consideration of DataRequirements for Structural Reliability Based Assessments of OnshorePipelines”, 5th International Conference on Engineering Structural IntegrityAssessment, Churchill College, Cambridge, UK September 2000.

[6] Francis, A., McCallum, M., Gardiner, M. & Michie, R., “A FundamentalInvestigation of the Effects of the Hydrostatic Pressure Test on the StructuralIntegrity of Pipelines using Structural Reliability Analysis”, 20th InternationalConference on Offshore Mechanics and Artic Engineering, Rio de Janeiro,Brazil, June 2001.

[7] McLamb, M., Hopkins P., Marley, M. & Nessim, M., “A Justification for Designingand Operating Pipelines upto Stresses of 80%SMYS”, 4th International PipelineConference, Calgary, Canada, October 2002

[8] Nessim, M., Zimmerman, T., Glover, A., McLamb, M., Rothwell, B. & Zhou, J.,“Reliability-based Limit States Design for Onshore Pipelines”, 4th InternationalPipeline Conference, Calgary, Canada, October 2002



[9] Francis, A., Gardiner, M., & McCallum, M., “Life Extension of a High PressureTransmission Pipeline Using Structural Reliability Analysis”, 4th InternationalPipeline Conference, Calgary, Canada, October 2002

[10] Francis, A., Gardiner, M., Goodfellow, A., McCallum, M., Senior, G. andGreenwood, B., “A systematic risk and reliability-based approach to integritymanagement of piggable and non-piggable pipelines”, Pipeline IntegrityManagement Conference, Houston, Texas, September, 2001.



Figure 1 Illustration of CIS Output

Figure 2 Illustration of DCVG Output

700

750

800

850

900

950

1000

0 50 100 150 200

Distance

Potential

Off PotentialOn Potential850 mV

Type III

Type II

Type I

0102030405060708090100

0 50 100 150 200

Distance

DCVG

0102030405060708090100

Defect

DCVGDefectHit

FalseIndication Miss



Change in Distribution of Number of Defects

0.00E+00

2.00E-02

4.00E-02

6.00E-02

8.00E-02

1.00E-01

1.20E-01

0 50 100 150

Nac

Prob

abili

ty

P(Nac)

P(Nac|Ncis)

P(Nac|Ncis&Ndcvg)

P(Nac|Ncis,Ndcvg,Ndigs)

Figure 3: Effect of CIPS, DCVG and Digs on Prior Distribution

Change in Failure Probability Using Above Ground Survey Results

1.00E-10

1.00E-08

1.00E-06

1.00E-04

1.00E-02

1.00E+00

1980 2000 2020 2040

Year

Prob

abili

ty

En = 98En = 72

Figure 4: Updated Failure Probability using Above Ground Methods



Distributions of Defects Found During Excavations after 20 years

0

2

4

6

8

10

12

1 2 3 4 5

Region

Freq

uenc

y

K=0.14

Figure 5: Defects found during excavations after 20 years

Change in Failure Probability Using Above Ground Survey and Bell-Hole Excavation Results

1.00E-10

1.00E-08

1.00E-06

1.00E-04

1.00E-02

1.00E+00

1980 2000 2020 2040

Year

Prob

abili

ty

K=0.2mm/yrK=0.14mm/yr

Figure 6: Updated failure probabilities

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