Third-Party Damage Model of a Natural Gas Pipeline Based on a Bayesian Network

Abstract

Natural gas plays an important role in the transition from fossil fuels to new energy sources. With the expansion of pipeline networks, there are also problems with the safety of pipeline network operations in the process of transportation. Among them, third-party damage is a key factor affecting the safety of pipelines. In this paper, the risk factors of third-party damage are analyzed, and an evaluation model of natural gas pipeline damage is established using the GeNIe Modeler. Through Bayesian network reverse reasoning and a maximum cause chain analysis from the four aspects of personnel, environment, management, and equipment, it was found that the top five factors that have significant influence on third-party damage, are safety investment, the completeness of equipment, safety inspection frequency, the management of residents along the pipeline, and safety performance, with the posteriori probability in the model of 97.3%, 95.4%, 95.2%, 95.1%, 95.1%, respectively. Consequently, it is necessary for pipeline operation companies to secure investment on safety, to make sure that the safety equipment (system) works and is in a good condition, to maintain the safety inspection frequency in an organization, to build a management system for residents along the pipeline, and to conduct routine safety performance assessments accordingly.