ORIGINAL RESEARCH article
Front. Earth Sci.
Sec. Geohazards and Georisks
Volume 13 - 2025 | doi: 10.3389/feart.2025.1639790
Risk Coupling Analysis of Underground Gas Storage Leakage Accidents Based on Dynamic Bayesian Network and N-K Model
Provisionally accepted
- 1College of Civil Aviation Safety Engineering, Civil Aviation Flight University of China, Guanghan, Sichuan, China, Sichuan, China
- 2College of Economics and Management, Civil Aviation Flight University of China, Guanghan, Sichuan, China, Sichuan, China
- 3Logistics service company, Civil Aviation Flight University of China, Guanghan, Sichuan, China, Sichuan, China
- 4School of Business, China University of Political Science and Law, Beijing, China
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Risk coupling (RC) analysis of underground gas storage (UGS) leakage accident risks is critical to overall natural gas storage safety. Consequently, the interactions among diverse risk factors need attention. This study proposes a novel methodology combining Dynamic Bayesian Networks (DBNs) and the N-K model to analyze RC in UGS leakage accidents. By integrating the N-K model's mutual information metric with DBN's temporal modeling, the approach achieves a mean absolute error (MAE) of 0.032 in predicting coupling probabilities and enables risk reduction of up to 17.4% through targeted interventions, enhancing the accuracy and actionable insights for UGS safety management. First, the causes of leakage accidents are systematically investigated, and risk categories are identified. Second, the categories of coupled risk arising from equipment, human, geological, and management factors are identified. Third, a DBN model is constructed based on leakage risk analysis and the N-K model. Fourth, the setting variables for RC nodes in the proposed DBN are identified through computational results using the N-K. Additionally, the validation of the proposed model is proven utilizing a three-axiom-based technique. The developed DBN effectively characterizes the dynamic evolution of leakage risks and RC mechanisms in UGS facilities. Furthermore, sensitivity analysis is implemented using the proposed model to investigate the impact of failure probabilities of risk factors on predominant RC types.
Keywords: Underground gas storage, Leakage accident, N-K model, Risk coupling, Dynamic Bayesian network
Received: 03 Jun 2025; Accepted: 10 Jul 2025.
Copyright: © 2025 Hu, Ding, Qiao, Gu and Yang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Yao Hu, College of Civil Aviation Safety Engineering, Civil Aviation Flight University of China, Guanghan, Sichuan, China, Sichuan, China
Mengqi Yang, School of Business, China University of Political Science and Law, Beijing, China
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