Evaluating the system reliability of corroding pipelines based on inspection data

Abstract

This paper presents a methodology for evaluating the time-dependent system reliability of a pressurised gas pipeline segment containing multiple active metal-loss corrosion defects. The methodology incorporates three distinctive failure modes of the pipe segment due to corrosion, namely small leak, large leak and rupture. The growth of the depth of individual corrosion defect is assumed to follow a power-law function of time. The Bayesian updating and Markov Chain Monte Carlo (MCMC) simulation techniques are used to quantify the parameters of the power-law growth model based on data obtained from multiple inspections carried out at different times. The simple Monte Carlo and MCMC techniques are combined to evaluate the system reliability. A numerical example involving an in-service gas pipeline located in Alberta, Canada, is used to illustrate the proposed methodology. Results of the sensitivity analysis suggest that the use of a defect-specific or segment-specific growth model for the defect depth has a marked impact on the evaluated system reliability. The proposed methodology can be incorporated in reliability-based pipeline corrosion management programmes to assist integrity engineers in making informed decisions about defect repair and mitigation.

Keywords::

• pipeline
• metal-loss corrosion
• system reliability
• inspection
• Bayesian updating and MCMC simulation

Acknowledgements

The authors gratefully acknowledge funding provided by TransCanada and the Natural Sciences and Engineering Research Council of Canada (NSERC) through the Collaborative Research and Development (CRD) programme and by the Faculty of Engineering at Western University. The assistance provided by Dr Shahani Kariyawasam from TransCanada and Shenwei Zhang from Western University is greatly appreciated. The authors also wish to thank the anonymous reviewer for his/her constructive comments.

Notes

^1. Email: [email protected].