Study on a failure probability prediction method based on failure data correction for natural gas pipelines

Failure probability prediction for natural gas pipelines differentiated between high consequence areas (HCA) and non-high consequence areas (Non-HCA) provides a scientific basis for developing differentiated safety management strategies, thereby facilitating a comprehensive enhancement of pipeline systems in terms of safety and reliability. Based on historical failure data of onshore natural gas pipelines in both HCAs and Non-HCAs, the analysis identified the main causes of failures and yielded average failure frequencies. By constructing an index system of influencing factors and combining it with a nonlinear fitting regression approach and fuzzy theory, a quantification process for these factors was developed. Moreover, their weights were calculated using the analytic hierarchy process. Building on these results, a failure probability prediction method based on failure data correction was ultimately established for natural gas pipelines. The results indicated that the average failure frequency of pipelines in HCAs was 1.52×10^-4 times·km^-1·a^-1, significantly higher than that in Non-HCAs (1.22×10^-4 times·km^-1·a^-1), with external disturbances and pipeline defects identified as the primary causes of failures. Through a case analysis, it was verified that this proposed method can accurately reflect risk characteristics for pipelines in different categories of areas, exhibiting strong operability and practicality. The study outcomes provide theoretical support for risk assessment, safety management, and the formulation of differentiated risk mitigation measures for natural gas pipelines, indicating potential for broad application in the risk assessment of other types of pipelines.