海上钻井
海底管道
钻探
贝叶斯网络
石油工程
工程类
海洋工程
事故(哲学)
风险分析(工程)
计算机科学
岩土工程
机械工程
业务
人工智能
哲学
认识论
作者
Wang Xing-zhong,Xinghua Kou,Jinfeng Huang,Wanli Wang
出处
期刊:Journal of physics
[IOP Publishing]
日期:2021-09-01
卷期号:2029 (1): 012143-012143
被引量:2
标识
DOI:10.1088/1742-6596/2029/1/012143
摘要
Abstract Offshore drilling operations has the characteristics of far offshore, harsh environment, high risk and great technical difficulty. It is difficult to deal with offshore drilling accidents, and it is easy to cause serious social and economic problems. Based on the risk records of drilling engineering, this paper analyzes the forms and causes of offshore drilling accidents, and establishes a dynamic Bayesian network analysis model for offshore drilling accidents. With the dynamic Bayesian network, the prediction probability of drilling risk is calculated. According to the blowout accident in offshore drilling, the analysis results show that the risk of blowout accident is is as high as 50.6%. The research results show that the method and the model presented in the paper is contributed to analysis and prevention of offshore drilling accidents.
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