TCPL IN-LINE INSPECTION MANAGEMENT PROGRAM. Patrick H. Vieth Kiefner & A ssociates, Inc. W orthington OH U nited S tates

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1 International Pipeline Conference Volum e I ASME 1998 IPC TCPL IN-LINE INSPECTION MANAGEMENT PROGRAM Patrick H. Vieth Kiefner & A ssociates, Inc. W orthington OH U nited S tates Reena Sahney and Blaine Ashworth TransCanada PipeLines Calgary AB T 2 P 3 Y 6 C A N A D A ABSTRACT TransCanada PipeLines (TCPL) has developed a formalized in-line inspection management program to encompass all aspects o f their inspection activities. The need for this formalized program w as recognized while implementing an aggressive inspection program planned through the year The formalized inspection management program developed by TCPL ensures consistent and thorough handling o f the data and maximizes the benefits o f conducting an in-line inspection. INTRODUCTION T ransc anada PipeLines (TCPL) operates approximately 14,000 km o f natural gas transmission pipelines. A majority o f their pipeline system is comprised o f up to six (6) parallel pipelines w hich are routed through southern portions o f Saskatchewan, Manitoba, Ontario, and Quebec. These pipelines were constructed and range in diameter from 762 mm to 1219 mm (30-inch to 48-inch). In 1994, TCPL experienced two line breaks attributable to external corrosion-caused metal loss (galvanic corrosion). These line breaks were the first major service failures due to corrosion in TC PL s history. These failures identified the system s susceptibility to external corrosion and the need for additional measures to assure the integrity o f the pipeline system. A corrosion risk assessment model was developed by TCPL and was used to prioritize in-line inspections. Based upon the results o f the risk assessment, a long range program was developed to inspect the entire pipeline system. This effort was directed tow ard the 10,000 km o f the pipeline system with external coating other than fusion bonded epoxy. Subsequent to the development of this long range program, a corrosion-caused service failure occurred in December, 1996 in a section of the pipeline system scheduled for inspection in In response to this failure, TCPL accelerated the in-line inspection program such that the entire pipeline system (except sections coated with fusion bonded epoxy) would be inspected by the end o f As a result o f this accelerated program, TCPL inspected over 3,700 km of their pipeline system in 1997 and has sim ilar aggressive inspection programs scheduled for 1998 and The level o f effort directed toward in-line inspection for corrosion has increased significantly over the past few years. The num ber o f inspections and kilometers o f pipe inspected each o f the past 4 years is summarized as follows: inspection 139 km inspections 66 km inspections 780 km inspections 3,700 km. TCPL recognized the need to develop a form alized in-line inspection management program in order to provide the level of effort required to complete the planned inspections, respond to the results provided by the inspections, and provide a high level o f confidence that the integrity o f the pipeline is achieved. Aspects of TCPL s in-line inspection managem ent program addressed within this paper are: - Prioritization for Inspection - Quality Assurance of the Inspection Data - Analysis o f the Inspection Data - Excavation Response Plan - Statistical Analysis o f Field Measurements and Inspection Data, and - Fitness for Service Report Copyright 1998 by ASME

2 Each o f these topics is briefly discussed below. PRIORITIZATION FOR INSPECTION The focal point o f TCPL s long range integrity plan is a risk assessment model referred to as TRPRAM (TransCanada P ipelines Risk Assessment Model). TRPRAM is a relative failure prediction model based on expert opinion o f factors that could contribute to integrity concerns such as external corrosion and thermal radiation consequences model. This model is similar to other risk assessment models used in the pipeline industry [1,2] in that the risk is the product o f the frequency o f an event and the anticipated consequences in the unlikely event o f failure. An algorithm was developed to model factors that could be used to identify locations most susceptible to external corrosion. Factors used include cathodic protection history, external coating type, soil aggressiveness, and age o f the pipeline. This algorithm produced a Corrosion Susceptibility Score (CSS) for each m ainline valve section. These scores were then adjusted to account for sections that had been hydrostatically tested, had been previously inspected using high resolution tools, and/or were located in areas where corrosion may be less of an integrity concern due to lower operating stress levels. The results o f this analysis produced a CSS between 0 and 110 for each mainline valve section. These CSS results were then ranked from highest to lowest and were used to prioritize and schedule inspections. Q UALITY ASSURANCE OF THE INSPECTION DATA TransCanada PipeLines (TCPL) contracted with British Gas Inspection Services (BGIS) to perform a majority o f their high resolution magnetic flux leakage (M FL) inspections through Other vendors such as Pipetronix, BJ Inspection Services, and HRosen continue to perform inspections as needed for various reasons. Since BGIS is contracted to conduct a significant portion o f the MFL inspections, TCPL decided to audit their procedures. The purpose of the audit was to assure that the highest level o f data quality and data analysis is achieved. The audit focused on procedures followed by BGIS from the commissioning of the tool prior to a launch through the production o f the final analysis reports. It should be noted that no significant problems were identified through this audit. However, this exercise did identify action items for both BGIS and TCPL to assure that the highest level o f data quality will continue to be supplied in the future and that the overall program is continually improved. ANALYSIS OF THE INSPECTION DATA In-line inspection vendors usually request pipeline operators to identify the interaction criterion and defect assessment criterion to be used in the assessment o f the corrosion features. The interaction criterion provides guidelines to determine whether corrosion features, located in close proximity to one another, should be considered to interact. The corrosion assessment criterion provides the means to calculate a predicted failure pressure for each corrosion feature based upon the amount o f missing metal (e.g., predicted depth and length o f the corrosion). The interaction criterion and corrosion assessment criterion have been modified since the in-line inspection program began in The criteria currently used by TCPL are described below. Interaction Criterion The methods for evaluating the corrosion features identified by an inspection differ between the various in-line inspection vendors. BGIS, for example, conducts an assessment o f the corrosion features through a two-step process. The first process, referred to as boxing, is an automated procedure where a box is drawn around each feature. Each pig call box has a predicted depth, axial length, and circumferential width. The second process, referred to as clustering, is an automated procedure which determines whether pig call boxes located in close proxim ity to another should be considered as a single corrosion feature. The interaction criterion employed by TCPL is that pig call boxes are considered to interact when they are located within 3t (3 times the nominal wall thickness) o f one another. For features located in pipe with a nominal wall thickness of 9.53 mm, pig call boxes are considered to interact when they are located within 28.6 mm The interaction criterion used in the clustering process is presented schematically in Figure 1. As shown in Figure 1A, each pig call box is expanded by 3t (3 times the nominal wall thickness) in all directions. In Figure 1 A, the pig call boxes are evaluated separately since the expanded pig call boxes do not overlap. However, as shown in Figure 1B, the expanded pig call boxes overlap and therefore the pig call boxes are considered to interact. Corrosion A ssessm ent Criterion The severity o f corrosion features identified by the inspection are assessed using the RSTRENG Corrosion Assessment Criterion [3,4,5]. The results o f this assessment are presented in terms o f a rupture pressure ratio, RPR, which is calculated as follows:

3 where: a a SM YS A RPR = - i -A I -A M * 1 A. = Flow Stress, (SMYS kpa) = Failure Stress, SMYS = Specified m inimum yield strength, kpa = Predicted area o f missing metal A, = O riginal area (L times t) L = Axial length o f cluster, mm D = Pipe diameter, mm M = Folias factor For A Dt 50, M ^ Dt For > 50, M = Dt Dt 0 ) t e ) ' (2) The screening procedure followed by TCPL involves the application o f this equation to calculate an RPR for each corrosion feature (i.e., cluster). An RPR equal to 1.00 corresponds to a predicted failure stress equal to the SMYS o f the pipe. The screening procedure followed by TCPL involves two types o f results produced by this assessment, RPRrstjsv. and RPRrst Em w hich are described below. The first step in the screening procedure is to calculate an RPR rst 85,4 (RSTRENG 85% Area Criterion) based on the predicted m axim um depth o f corrosion, d, and axial length o f corrosion, L. In this assessment, A/A in Equation 1 is defined to be 0.85 d/t. The second step in the screening procedure is to calculate an RPRrst Efr (RSTRENG Effective A rea Criterion) for all features with an RPRRSt_85% less than or equal to This analysis, referred to as a LAPA Assessment, is conducted by establishing a profile o f the area o f corrosion from the pig data. In this assessment, A/A in Equation 1 is defined based on the predicted profile o f the missing metal. The iterative calculation embodied within the RSTRENG Effective Area assessment is conducted along the predicted profile. The only difference between the RPRrst i5% and RPRrst Efr is the m anner in which the area o f missing metal is modeled; 0.85d/t or the predicted profile o f corrosion. The RPRrst Efr assessment (LAPA corrosion profile) uses all o f the available data provided by the tool to best characterize the area o f missing metal. This approach is certainly reasonable to prioritize a response plan and further work is underway to quantify the level o f conservatism em bodied in this approach. EXCAVATION RESPONSE PLAN An overview o f the inspection program followed by TCPL through 1997 is presented in Figure 2. Each o f these procedures is described below. V endor Provides Preliminary Report TCPL requires that a Preliminary Report be provided within 10 days o f completing the inspection. This Preliminary Report identifies corrosion features with predicted depths greater than 70% o f the wall thickness and features with an RPR rst 8S%less than Those features with an RPR rst S5% less than 1.00 are then subjected to a more detailed analysis referred to as a LAPA Assessment and provides a calculated R PR rst eh- Phase I Preliminary Dias The purpose o f the Phase I digs is to immediately excavate locations that could produce a failure in the near future. These digs are initiated upon receipt o f the Preliminary Report and are completed within a maximum o f 60 days. Locations where either the predicted depth is greater than 70% o f the wall thickness or the RPR rst eit is less than 1.00 (e.g., predicted failure stress level less than 100% o f SMYS) are identified in the Preliminary Report. The features identified to be most significant (predicted depth greater than 70% o f the wall thickness or RPRrst ot less than 0.90) are the highest priority and a pressure reduction may be imposed to assure the integrity o f the line until the excavations are completed. Vendor Provides Final Report (6 0 davsl A final report is provided by the vendor within 60 days o f completing the inspection. It should be noted that m ost o f the excavations have either been completed or are in progress by the time the Final Report is provided by the vendor. Follow U p Analysis - Phase II Dios Once the final report is received, it is reviewed to identify any changes from the Preliminary Report. Additional analyses are conducted to identify any other characteristics o f the results. One type o f analysis is to evaluate the density o f pig calls along the line. These results may identify problematic areas such as a location o f general coating failure. Even though the corrosion features may not be severe, a high density may identify problematic locations. Figures 3 and 4 provide a distribution o f the num ber of features reported over a 0.5 km span for two valve sections. In these figures, the number o f reported features within each 0.5 km span is summed and plotted versus the distance (in kilometers) from the upstream mainline valve. It should be noted that many o f the reported corrosion features are near the detection threshold o f the tool.

4 In Figure 3, the num ber o f features within each 0.5 km span is relatively constant along the valve section. These results can be com pared to Figure 4 where the number o f features is greater between 10 km and 20 km. Results such as that provided in Figure 3 can be used to identify locations where additional attention may be warranted. For example, the location between 10 km and 20 km can be considered for an alternative remediation program such as cathodic protection system upgrades or possibly even recoating. Results such as those presented in Figure 3 and 4 are used to evaluate the density o f corrosion features over a defined length. However, this type o f analysis does not account for the severity of the corrosion in these areas, although this can be done. The program described above has proven to be an effective program to identify and remediate areas o f corrosion. One aspect of this program that will be reviewed in the future is the Preliminary Reporting requirement. A considerable level o f effort is required to develop these reports and to identify- the locations (chainage) to excavate in the absence o f a completed Final Features Report. STA TISTIC A L ANALYSIS OF FIELD M EASUREMENTS AND EXCAVATION DATA Statistical m ethods have been developed [6,7] to evaluate the density o f corrosion and the severity of corrosion over areas o f the pipeline. The results o f these analyses can be used in many applications such as providing the ability to quantify the added value o f additional excavations. The results o f these analyses are presented in terms o f Probability o f Exceedance or POE. The probability o f exceedance evaluates the likelihood that, based on the predicted depth and axial length o f a corroded area, the predicted failure pressure is less than the maximum operating pressure (MOP). The probability o f exceedance results are best explained using the schematic presented in Figure 5. In this figure, a profile o f a typical corrosion feature is presented along with it s associated axial length, L, and predicted depth, d. The dashed line presented below this profile represents the critical depth o f corrosion; a depth o f corrosion that would produce a predicted failure pressure equal to the MOP. Therefore, the probability o f exceedance (PO E) evaluates the likelihood that the predicted depth o f corrosion exceeds the critical depth of corrosion (i.e., the predicted failure pressure is less than the MOP). The critical depth o f corrosion is never permitted to be greater than 80% o f the wall thickness to prevent against the possibility of a leak. One benefit o f producing POE results is that individual results can be com bined to evaluate the POE for any defined length. For exam ple, assume that 30 corrosion features are identified on a single joint o f pipe. The POE for the pipe joint can be calculated as follows: POEPipeJoint= 1 - ( 1 - P,) ( 1 - P 2)..(1 -P 30) (3) where P; is the POE for each corrosion feature. The POE for each corrosion feature, Pif is determined from the analysis results. For example, assume that based upon the pipe geometry, material grade, and operating pressure that the maximum allowable depth o f corrosion is 50% wall loss. The associated corrosion feature has a predicted depth o f 30% wall loss and 6-inches in length. The probability that the actual depth is greater than 50% wall loss is 6.3 x 10^* (POE is 6.3 x lo"**. Once a POE has been calculated for each corrosion feature, the results can be summarized in any number ways depending on how the results will be applied. One application o f the results is to calculate a POE for each joint (POE,oinl) and rank these results from highest to lowest POE. These results can be plotted in a manner sim ilar to that presented in Figure 6. Each X plotted in Figure 6 represents the POE associated with a particular joint o f pipe for the 50 pipe joints with the highest POE. The solid line represents the cum ulative POE for the entire section considered within this analysis (e.g., several mainline valve sections). These type o f results can be used to evaluate the added value o f additional excavations. For example, the maximum POE for each pipe joint can be reduced by an order o f magnitude by com pleting 7 excavations. These results also show that at least 22 additional excavations would be required to reduce the maximum POE by an additional order o f magnitude. These results provide TCPL with an additional tool to evaluate various remediation projects across their entire pipeline system. For example, the POE results for one m ainline valve section can be compared to other mainline valve sections such that the most appropriate response plan is developed. These results are certainly applicable in a relative manner across the entire pipeline system. However, the absolute value o f the POE results is believed to be conservative based upon the excavations com pleted to date. Further work is currently underway to better estimate actual POE values. The statistical methods employ ed to develop these type o f results are not described within this paper but have been presented previously [6,7]. These analysis methods incorporate pig performance characteristics such as detection capabilities and depth accuracy measurements. These performance characteristics are quantified by comparing the results provided by the inspection to measurements o f actual corrosion measured in field from subsequent excavations. FITNESS FOR SERVICE REPORT TCPL has developed a Fitness for Service Report (FSR) that is produced once a section o f their pipeline system has been inspected and remediated. The development o f this report involves a review of the in-line inspection results and subsequent excavations. This review and development o f the FSR provides

5 additional assurance that appropriate procedures have been followed and that based on the available information, the pipeline section is fit for continued service. S U M M A R Y TCPL is in the m idst o f an aggressive MFL inspection program planned through the year In order to maximize the results produced by this program, TCPL has developed a formalized M FL in-line inspection program to ensure consistent and thorough handling o f the data and to maximize the benefits o f conducting an in-line inspection. As with all in-line inspection programs, the procedures and methods employed in this program will be updated when additional information is obtained and the process will be continually improved. For example, the CSS scoring system was used for prioritizing the 1997 inspection program and for planning future corrosion remediation activities. The results o f the com pleted MFL runs and output such as the POE results m ay either supplement or replace the CSS scoring system in the future. 4. Kiefner, J.F., and Vieth, P.H., A Modified Criterion for Evaluating the Remaining Strength o f Corroded Pipe, PRC/ntemational/American Gas Association, Catalog No. L51609, Vieth, P.H., and Kiefner, J.F., RSTRENG User's Manual", PRC/ntemational/American Gas Association, Catalog No. L S I688, March Vieth, P.H., Rust, S.W., Johnson, E.R., and Cox, M.J., Corrosion Pig Performance Evaluation, CORROSION/96, National Association o f Corrosion Engineers (NACE), Denver, Colorado, M arch Rust, S.W., Vieth, P.H., Johnson, E.R., and Cox, M.J., Quantitative Corrosion Risk Assessment Based on Pig Data, CORROSION/96, National Association o f Corrosion Engineers (NACE), Denver, Colorado, March ACKNOW LEDGMENTS The authors would like to acknowledge the contributions o f Steven W. Rust and Fred Todt o f Battelle, Columbus, Ohio. Steve and Fred have provided expertise in the development o f the statistical analysis techniques for in-line inspection data. REFERENCES 1. K iefner, J.F., Vieth, P.H., Orban, J.E., and Feder, P.I., M ethods for Prioritizing Pipeline Maintenance and Rehabilitation, PRC /ntem ational/american Gas Association, Catalog N o. L51631, Septem ber Bash, S.D., and Kiefner, J.F., et al., Pipeline Risk M anagem ent Utilizing the Pipeline Prioritization M odel, Pipeline Risk Assessment, Rehabilitation and Repair Conference, O rganized by Pipe Line Industry and Pipes & Pipelines Intem ational/g ulf Publishing, Houston, Texas, September M uhlbauer, W.K., RIPS Identifies Pipeline Risks, Pipeline Risk Assessment, Rehabilitation and Repair Conference, O rganized by Pipe Line Industry and Pipes & Pipelines Intem ational/g ulf Publishing, Houston, Texas, May 20-23, 1991.

6 Original Pig Call Box Expanded Pig Call Box Figure 1A. Sample of Pig Call Boxes that are considered Separate Original Pig Call Box Expanded Pig Call Box Figure 1B. Sample of Pig Call Boxes that are considered to Interact

7 Figure 2. TCPL's MFL Inspection Program

8 g Uditive DbUnce, km Figure 3. Density of Corrosion Features

9 î < Length > 365 Figure 5. Schematic of Corrosion Profile

10 Rank by Joint Probability of Exceedance, POE Figure 6. Sample of Probability of Exceedance Results for the Top 50 Locations