0
Research Papers: Design and Analysis

Time-Dependent Corrosion Growth Modeling Using Multiple In-Line Inspection Data

[+] Author and Article Information
Shenwei Zhang

Department of Civil and
Environmental Engineering,
Western University,
London, ON N6A 5B9, Canada
e-mail: szhan85@ uwo.ca

Wenxing Zhou

Assistant Professor
Department of Civil and
Environmental Engineering,
Western University,
London, ON N6A 5B9, Canada
e-mail: wzhou@eng.uwo.ca

Mohammad Al-Amin

Engineer-in-Training
TransCanada Corporation,
450-1st Street SW,
Calgary, AB T2P 5H1, Canada
e-mail: mohammad_al-amin@transcanada.com

Shahani Kariyawasam

Principal Engineer
TransCanada Corporation,
450-1st Street SW,
Calgary, AB T2P 5H1, Canada
e-mail: shahani_kariyawasam@transcanada.com

Hong Wang

Risk Engineer
TransCanada Corporation,
450-1st Street SW,
Calgary, AB T2P 5H1, Canada
e-mail: hong_wang@transcanada.com

1Corresponding author.

Contributed by the Pressure Vessel and Piping Division of ASME for publication in the JOURNAL OF PRESSURE VESSEL TECHNOLOGY. Manuscript received November 26, 2012; final manuscript received February 5, 2014; published online April 16, 2014. Assoc. Editor: Roman Motriuk.

J. Pressure Vessel Technol 136(4), 041202 (Apr 16, 2014) (7 pages) Paper No: PVT-12-1177; doi: 10.1115/1.4026798 History: Received November 26, 2012; Revised February 05, 2014

This paper describes a nonhomogeneous gamma process-based model to characterize the growth of the depth of corrosion defect on oil and gas pipelines. All the parameters in the growth model are assumed to be uncertain; the probabilistic characteristics of these parameters are evaluated using the hierarchical Bayesian methodology by incorporating the defect information reported by the multiple in-line inspections (ILIs) as well as the prior knowledge about these parameters. The bias and random measurement error associated with the ILI tools as well as the correlation between the measurement errors associated with different ILI tools are taken into account in the analysis. The application of the model is illustrated using an example involving real ILI data on a pipeline that is currently in service. The results suggest that the model in general can predict the growth of corrosion defects reasonably well. The proposed model can be used to facilitate the development and application of reliability-based pipeline corrosion management.

FIGURES IN THIS ARTICLE
<>
Copyright © 2014 by ASME
Your Session has timed out. Please sign back in to continue.

References

CoshamA., HopkinsP., and Macdonald, K. A., 2007, “Best Practice for the Assessment of Defects in Pipelines-Corrosion,” Eng. Fail. Anal., 14(7), pp. 1245–1265. [CrossRef]
Kariyawasam, S., and Peterson, W., 2008, “Revised Corrosion Management With Reliability Based Excavation Criteria,” Proceedings of IPC 2008, ASME, Calgary, Paper No. IPC2008-64536. [CrossRef]
Nessim, M. A., Zhou, W., Zhou, J., Rothwell, B., and McLamb, M., 2009, “Target Reliability Levels for Design and Assessment of Onshore Natural Gas Pipelines,” ASME J. Pressure Vessel Technol., 131(6), p. 061701. [CrossRef]
Nessim, M. A., Zhou, W., Zhou, J., and Rothwell, B., 2009, “Reliability Based Design and Assessment for Location-Specific Failure Threats With Application to Natural Gas Pipelines,” ASME J. Pressure Vessel Technol., 131(4), p. 041701. [CrossRef]
Zhou, J., Rothwell, B., Nessim, M. A., and Zhou, W., 2009, “Reliability-Based Design and Assessment Standards for Onshore Natural Gas Transmission Pipelines,” ASME J. Pressure Vessel Technol., 131(3), p. 031702. [CrossRef]
Nessim, M. A., Dawson, J., Mora, R., and Hassanein, S., 2008, “Obtaining Corrosion Growth Rates From Repeat In-Line Inspection Runs and Dealing With the Measurement Uncertainties,” Proceedings of IPC 2008, ASME, Calgary, Paper No. IPC2008-64378.
AhammedM., and MelchersR. E., 1996, “Reliability Estimation of Pressurised Pipelines Subject to Localised Corrosion Defects,” Int. J. Pressure Vessels Piping, 69(3), pp. 261–272. [CrossRef]
AhammedM., 1998, “Probabilistic Estimation of Remaining Life of a Pipeline in the Presence of Active Corrosion Defects,” Int. J. Pressure Vessels Piping, 75(4), pp. 321–329. [CrossRef]
PandeyM. D., 1998, “Probabilistic Models for Condition Assessment of Oil and Gas Pipelines,” NDT&E Int., 31(5), pp. 349–358. [CrossRef]
AmiratA., Mohamed-ChateauneufA., and ChaouiK., 2006, “Reliability Assessment of Underground Pipelines Under the Combined Effect of Active Corrosion and Residual Stress,” Int. J. Pressure Vessels Piping, 83(2), pp. 107–117. [CrossRef]
Stephens, M., and Nessim, M. A., 2006, “A Comprehensive Approach to Corrosion Management Based on Structural Reliability Method,” Proceedings of IPC2006, ASME, Calgary, Paper No. IPC06-10458. [CrossRef]
TeixeiraA. P., Guedes SoaresC., NettoT. A., and Estefen, S. F., 2008, “Reliability of Pipelines With Corrosion Defects,” Int. J. Pressure Vessels Piping, 85(4), pp. 228–237. [CrossRef]
ZhouW., 2010, “System Reliability of Corroding Pipelines,” Int. J. Pressure Vessels Piping, 87(10), pp. 587–595. [CrossRef]
Kariyawasam, S., and Peterson, W., 2010, “Effective Improvements to Reliability Based Corrosion Management,” Proceedings of IPC 2010, ASME, Calgary, Paper No. IPC2010-31425. [CrossRef]
Maes, M. A.Faber, M. H., and Dann, M. R., 2009, “Hierarchical Modeling of Pipeline Defect Growth Subject to ILI Uncertainty,” Proceedings of the ASME 28th International Conference on Ocean, Offshore and Arctic Engineering, Honolulu, Hawaii, Paper No. OMAE2009-79470. [CrossRef]
Yuan, X. X., Mao, D., and Pandy, M. D., 2009, “A Bayesian Approach to Modeling and Predicting Pitting Flaws in Stream Generator Tubes,” Reliab. Eng. Syst. Saf., 94(11), pp. 1838–1847. [CrossRef]
Al-Amin, M., Zhou, W., Zhang, S., Kariyawasam, S., and Wang, H., 2012, “Bayesian Model for the Calibration of ILI Tools,” Proceedings of IPC 2012, ASME, Calgary, Paper No. IPC2012-90491. [CrossRef]
Pandey, M. D., Yuan, X., and van Noortwijk, J. M., 2005, “Gamma Process Model for Reliability Analysis and Replacement of Aging Structural Components,” Proceedings ICOSSAR, Rome, Italy, Paper No. 311.
Pandey, M. D., Yuan, X. X., and van Noortwijk, J. M., 2009, “The Influence of Temporal Uncertainty of Deterioration on Life-Cycle Management of Structures,” Struct. Infrastruct. Eng., 5(2), pp. 145–156. [CrossRef]
van Noortwijik, J. M., van der Weide, J. A. M., Kallen, M. J., and Pandy, M. D., 2007, “Gamma Process and Peaks-Over-Threshold Distribution for Time-Dependent Reliability,” Reliab. Eng. Syst. Saf., 92(12), pp. 1651–1658. [CrossRef]
van Noortwijik, J. M., 2009, “A Survey of the Application of Gamma Process in Maintenance,” Reliab. Eng. Syst. Saf., 94(1), pp. 2–21. [CrossRef]
Maes, M. A., and Dann, M. R., 2008, “Hierarchical Bayes Methods for Systems With Spatially Varying Condition States,” Can. J. Civil Eng., 34(10), pp. 1289–1298. [CrossRef]
Maes, M. A., Dann, M. R., Breitung, K. W., and Brehm, E., 2008, “Hierarchical Modeling of Stochastic Deterioration,” Proceeding of the 6th International Probabilistic Workshop, Darmstadt, Germany.
Provan, J. W., and RodriguezIII, E. S., 1989, “Part I: Development of Markov Description of Pitting Corrosion,” Corrosion, 45(3), pp. 178–192. [CrossRef]
Hong, H. P., 1999, “Application of Stochastic Process to Pitting Corrosion,” Corrosion, 55(1), pp. 10–16. [CrossRef]
Hong, H. P., 1999, “Inspection and Maintenance Planning of Pipeline Under External Corrosion Considering Generation of New Defects,” Struct. Saf., 21(3), pp. 203–222. [CrossRef]
Valor, A., Caleyo, F., Alfonso, L., Rivas, D., and Hallen, J. M., 2007, “Stochastic Modeling of Pitting Corrosion: A New Model for Initiation and Growth of Multiple Corrosion Pits,” Corros. Sci., 49(2), pp. 559–579. [CrossRef]
Caleyo, F., Velázquez, J. C., Valor, A., and Hallen, J. M., 2009, “Markov Chain Modelling of Pitting Corrosion in Underground Pipelines,” Corros. Sci., 51(9), pp. 2197–2207. [CrossRef]
Timashev, S. A., Malyukova, M. G., Poluian, L. V., and Bushinskaya, A. V., 2008, “Markov Description of Corrosion Defects Growth and Its Application to Reliability Based Inspection and Maintenance of Pipelines,” Proceedings of IPC 2008, ASME, Calgary, Paper No. IPC2008-64546. [CrossRef]
Little, J., Goldstein, M., and Jonathan, P., 2004, “Spatio-Temporal Modelling of Corrosion in An Industrial Furnace,” Appl. Stoch. Model. Bus., 20(3), pp. 219–238. [CrossRef]
Little, J., Goldstein, M., Jonathan, P., and den Heijer, K., 2004, “Efficient Bayesian Sampling Inspection Processes Based on Transformed Spatio-Temporal Data,” Stat. Model., 4(4), pp. 299–313. [CrossRef]
Bunea, C., Charitos, T., Cooke, R. M., and Becker, G., 2005, “Two-Stage Bayesian Models: Application to ZEDB Project,” Reliab. Eng. Syst. Saf., 90(2–3), pp. 123–130. [CrossRef]
Celeux, G., Persoz, M., Wandji, J. N., and Perrot, F., 1999, “Using Markov Chain Monte Carlo Method to Solve Full Bayesian Modeling of PWR Vessel Flaw Distributions,” Reliab. Eng. Syst. Saf., 66(3), pp. 243–252. [CrossRef]
West, M., and Harrison, J., 1989, Bayesian Forecasting and Dynamic Models, Springer-Verlag, NY.
Randell, D., Goldstein, M., Hardman, G., and Jonathan, P., 2010, “Bayesian Linear Inspection Planning for Large-Scale Physical Systems,” Proc. Inst. Mech. Eng., Part O, 224, pp. 333–345. [CrossRef]
Wang, J., and Liu, X., 2010, “Evaluation and Bayesian Dynamic Prediction of Deterioration of Structural Performance,” Struct. Infrastruct. Eng., 6(6), pp. 663–674. [CrossRef]
Banerjee, S., Carlin, B. P., and GelfandA. E., 2004, Hierarchical Modeling and Analysis for Spatial Data, Chapman and Hall/CRC, Boca Raton, FL.
Ang, A. H. S., and Tang, W. H., 1975, Probability Concepts in Engineering Planning and Design, Volume I: Basic Principles, John and Wiley & sons, NY.
Jonhson, R. A., 2000, Probability and Statistics for Engineers, 6th ed., Prentice-Hall, Inc., NJ.
Yuan, X. X., Pandey, M. D., and Bickelb, G. A., 2008, “A Probabilistic Model of Wall Thinning in CANDU Feeders Due to Flow-Accelerated Corrosion,” Nucl. Eng. Des., 238(1), pp. 16–24. [CrossRef]
Cheng, T., and Pandey, M. D., 2012, “An Accurate Analysis of Maintenance Cost of Structures Experiencing Stochastic Degradation,” Struct. Infrastruct. Eng., 8(4), pp. 329–339. [CrossRef]
Tanner, M. A., and Wong, W. H., 1987, “The Calculation of Posterior Distributions by Data Augmentation,” J. Am. Stat. Assoc., 82(398), pp. 528–540. [CrossRef]
Press, S. J., 2003, Subjective and Objective Bayesian Statistics: Principles, Models, and Applications2nd ed., Wiley-Interscience, NJ.
Gelman, A., Carlin, J. B., Stern, H. S., and Rubin, D. B., 2003, Bayesian Data Analysis, 2nd ed., Chapman & Hall/CRC, Boca Raton, FL.
Congdon, P., 2003, Applied Bayesian Modeling, John Wiley and Sons, Ltd., NJ.
Neal, R. M., 2003, “Slice Sampling,” Ann. Stat., 31(3), pp. 705–767. [CrossRef]
Jasa, T., and Xiang, N., 2009, “Efficient Estimation of Decay Parameters in Acoustically Coupled-Spaces Using Slice Sampling,” J. Acoust. Soc. Am., 126(3), pp. 1269–1279. [CrossRef]
Lunn, D., Spiegelhalter, D., Thomas, A., and Best, N., 2009, “The BUGS Project: Evolution, Critique and Future Directions (With Discussion),” Stat. Med., 28(25), pp. 3049–3082. [CrossRef]
Pipeline Operators Forum (POF), 2009, “Specifications and Requirements for Intelligent Pig Inspection of Pipelines,” Version2009.
Aziz, P. M., 1956, “Application of the Statistical Theory of Extreme Values to the Analysis of Maximum Pit Depth Data for Aluminum,” Corrosion, 12(10), pp. 495–506.

Figures

Grahic Jump Location
Fig. 1

Structure of the hierarchical Bayesian corrosion growth model

Grahic Jump Location
Fig. 2

Apparent growth paths of individual defects characterized by the ILI-reported and field-measured depths

Grahic Jump Location
Fig. 3

Comparison of the predicted depth with the field measure depth in 2010

Grahic Jump Location
Fig. 4

Predicted defect depth growth from the year of defect initiation up to 2010

Grahic Jump Location
Fig. 5

Time-dependent PDF for the depth of defect #2

Grahic Jump Location
Fig. 6

PDF curves for the depth of defects #1–#10 in 2009

Tables

Errata

Discussions

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In