<p>The long-distance pipeline is the crucial connection for oil &amp; gas&nbsp;producing area and demand&nbsp;location, but the pipeline may be damaged due to the impact of various factors, resulting in the leakage of oil and gas. Reliable failure assessment can avoid the occurrence of pipeline leakage and reduce losses effectively. In this paper, a method based on fuzzy Bayesian Network and AHP&nbsp; is proposed for failure evaluation of pipeline. In the&nbsp;proposed model, the influence factors (basic events) of pipeline failure are obtained by literature, database and expert questionnaire. The prior probabilities of basic events are calculated by combining expert opinion and fuzzy theory&nbsp;to overcome the shortage of pipeline history database, then the AHP is adopted to analysis the conditional probability. Finally, the relationship between events, prior probability and conditional probability are transported to Bayesian Network for inductive inference. The posterior probability and critical events are analysis through GeNIe. The model is applied to Fletcher Hayes Strait of China-Myanmar gas pipeline to prove the feasibility and rationality of the model, and the failure probability of this pipeline is 2.487E-04. According to the diagnostic function of Bayesian Network, the critical&nbsp;events that caused the failure of this&nbsp;pipeline are river erosion, microbial corrosion, material defects, structural defects, construction defects and welding defects.The result indicates that the proposed model can help pipeline operators to&nbsp;evaluate the probability of&nbsp;pipeline failure,&nbsp; identify the critical factors of pipeline failure and provide guidance for the safety of oil &amp; gas pipelines.</p>

Failure Assessment of Gas Pipeline Based on Fuzzy Bayesian Network and AHP

Paper Proceedings: https://asmedigitalcollection.asme.org/PVP/PVP2021/volume/85314

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