Session: OAC-01-01 Safety, Reliability, and Risk Management

Paper Number: 154405

154405 - A Comprehensive Accident Model for Natural Gas Processing Stations: Integrating Improved Shipp Model With Bayesian Networks for Dynamic Risk Prediction 

Abstract: 

Natural gas processing stations are a crucial component in the production and transportation processes of the oil industry, serving as key hubs for gas processing, storage, and distribution. Currently, there is a lack of comprehensive accident models specifically designed for natural gas processing systems, and few studies have systematically analyzed the interdependencies of safety barriers. This paper improves the System Hazard Identification, Prediction, and Prevention (SHIPP) model by incorporating the operational characteristics and accident features of natural gas processing stations, establishing a full-process accident model based on the improved SHIPP model. General fault tree models were developed for key prevention stages, including leakage prevention, diffusion prevention, ignition prevention, escalation prevention, and harm control and emergency management, describing the failure modes of various safety barriers. A cause-consequence relationship model was constructed by combining fault trees and event trees, which were then mapped to Bayesian networks to represent uncertainty and conditional dependencies. Bayesian network updating mechanisms were used to update probabilities based on new evidence, and Bayesian theory was applied to learn from abnormal event data, reducing the uncertainty of prior probabilities and enabling dynamic risk prediction for accidents at natural gas processing stations. The application of this model to accident analysis in a natural gas processing station demonstrated its effectiveness and accuracy in reconstructing accident processes and revealing causal relationships. The results show that the proposed model provides an essential tool for accident investigation and analysis, offering scientific guidance and decision-making support for risk prediction and accident prevention at natural gas processing stations.

Presenting Author: Shuyi Xie State Key Laboratory of Oil and Gas Equipment, CNPC Tubular Goods Research Institute

Presenting Author Biography: Dr. Shuyi Xie, born in August 1994, received his Ph.D. in Safety Science and Engineering from China University of Petroleum (Beijing) in 2021. He is currently affiliated with the State Key Laboratory of Oil and Gas Equipment at the CNPC Tubular Goods Research Institute, where his research focuses on the integrity management of oil and gas storage and transportation facilities. Dr. Xie has authored more than 10 peer-reviewed SCI papers in the areas of risk assessment and safety evaluation for oil and gas infrastructure, with over 200 citations on Google Scholar. His contributions have advanced safety practices in the industry, providing valuable insights into the management of critical energy assets.

Authors:

Shuyi Xie State Key Laboratory of Oil and Gas Equipment, CNPC Tubular Goods Research Institute
Jinheng Luo State Key Laboratory of Oil and Gas Equipment, CNPC Tubular Goods Research Institute
Gang Wu State Key Laboratory of Oil and Gas Equipment, CNPC Tubular Goods Research Institute
Kangkai Xu State Key Laboratory of Oil and Gas Equipment, CNPC Tubular Goods Research Institute