A fuzzy Bayesian belief network for safety assessment of oil and gas pipelines

Abstract

Safety assessment of oil and gas (O&G) pipelines is necessary to prevent unwanted events that may cause catastrophic accidents and heavy financial losses. This study develops a safety assessment model for O&G pipeline failure by incorporating fuzzy logic into Bayesian belief network. Proposed fuzzy Bayesian belief network (FBBN) model explicitly represents dependencies of events, updating probabilities and representation of uncertain knowledge (such as randomness, vagueness and ignorance). The study highlights the utility of FBBN in safety analysis of O&G pipeline because of its flexible structure, allowing it to fit a wide variety of accident scenarios. The sensitivity analysis of the proposed model indicates that construction defect, overload, mechanical damage, bad installation and quality of worker are the most significant causes for the O&G pipeline failures. The research results can help owners of transmission and distribution pipeline companies and professionals to prepare preventive safety measures and allocate proper resources.

Keywords:

• Oil and gas pipelines
• Safety assessment
• Bayesian belief network (BBN)
• Fault tree analysis (FTA)
• Fuzzy set theory
• Linguistic variables
• Uncertainty

Acknowledgements

The financial support from Natural Sciences and Engineering Research Council of Canada (NSERC) under Discovery Grant Program and CRD grant for second and third authors is acknowledged.

Disclosure statement

No potential conflict of interest was reported by the authors.