关键词: 大牛地气田, 动态贝叶斯网络, 风险评估, 敏感性分析

Abstract: In order to effectively address the risk management challenges in preventing leakage accidents in the long-distance pipelines of Daniudi Gas Field, this study proposes a dynamic risk assessment method based on Bayesian Network (BN). First, risk factors in the leakage accident process of gas field pipelines were identified and the consequences of leakage evolution were visualized using the Event Sequence Diagram method. Subsequently, a Dynamic Bayesian Network (DBN) model was developed to characterize the pipeline leakage failure evolution. By incorporating fuzzy set theory to quantify the basic event probabilities of uncertain factors, the model dynamically captured the risk evolution characteristics of pipeline leakage accidents. Finally, dynamic probability analysis of accidents was employed to evaluate the risk probability of pipeline leakage in the gas field. The results indicate that this method can efficiently identify the critical risk factors of leakage accidents in Daniudi Gas Field pipelines and has realized the dynamic risk assessment of long-distance pipelines in the gas field.

Key words: Daniudi gas field, dynamic Bayesian network (DBN), risk assessment, sensitivity analysis