基于风险熵和复杂网络的深水钻井井喷事故风险演化评估

孟祥坤; 陈国明; 郑纯亮; 吴翔飞; 朱高庚

doi:10.11949/j.issn.0438-1157.20180501

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基于风险熵和复杂网络的深水钻井井喷事故风险演化评估

过程安全 | 更新时间：2020-06-24

- 基于风险熵和复杂网络的深水钻井井喷事故风险演化评估
- Risk evaluation model of deepwater drilling blowout accident based on risk entropy and complex network
- 化工学报 2019年70卷第1期页码：388-397
- 作者机构：
  
  1.中国石油大学（华东）海洋油气装备与安全技术研究中心，山东青岛 266580
  2.海洋石油工程（青岛）有限公司，山东青岛 266520
- 作者简介：
  
  孟祥坤（1988—），男，博士研究生，wsdy1002@163.com
  陈国明（1962—），男，博士，教授，offshore@126.com
- 基金信息：
  
  国家重点研发计划重点专项项目(2017YFC0804501);国家工信部第七代超深水钻井平台创新专项项目(工信部联装【2016】24号);长江学者和创新团队发展计划项目(IRT_14R58)
- DOI：10.11949/j.issn.0438-1157.20180501
  中图分类号： TE 58
- 收稿：2018-05-14，
  
  修回：2018-06-21，
  
  纸质出版：2019-01-05
- 稿件说明：
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孟祥坤, 陈国明, 郑纯亮, 吴翔飞, 朱高庚. 基于风险熵和复杂网络的深水钻井井喷事故风险演化评估[J]. 化工学报, 2019, 70(1): 388-397

MENG Xiangkun, CHEN Guoming, ZHENG Chunliang, WU Xiangfei, ZHU Gaogeng. Risk evaluation model of deepwater drilling blowout accident based on risk entropy and complex network[J]. CIESC Journal, 2019, 70(1): 388-397
孟祥坤, 陈国明, 郑纯亮, 吴翔飞, 朱高庚. 基于风险熵和复杂网络的深水钻井井喷事故风险演化评估[J]. 化工学报, 2019, 70(1): 388-397 DOI： 10.11949/j.issn.0438-1157.20180501.

MENG Xiangkun, CHEN Guoming, ZHENG Chunliang, WU Xiangfei, ZHU Gaogeng. Risk evaluation model of deepwater drilling blowout accident based on risk entropy and complex network[J]. CIESC Journal, 2019, 70(1): 388-397 DOI： 10.11949/j.issn.0438-1157.20180501.

摘要

针对深水钻井作业安全问题，基于风险熵和复杂网络理论，在考虑风险不确定性的基础上，提出深水钻井井喷事故风险演化量化评估方法。依据深水钻井流程，构建井喷事故场景复杂网络演化模型，判断节点聚类性；针对风险传递的随机性与模糊性，引入风险熵表征两类不确定性；给出风险传递路径最大可能性的表达式，并转化为线性规划问题，通过Dijkstra算法得出事故最短路径。结果表明：深水井喷事故复杂网络的聚类系数为0.132，节点聚集程度较低而演化性较强，具有小世界网络特征；以自然因素类的钻遇浅层气作为初始事件的风险传递路径对井喷事故的影响最大，但所有初始事件的风险经少数几步传递即可导致井喷事故的发生，验证该方法在复杂过程系统定量风险评估方面的可行性。

Abstract

To control the cascading risk of deepwater blowout

a quantitative evaluation method associated with risk uncertainty and evolution of deepwater drilling system was proposed

based on risk entropy theory and complex network theory. The complicated accident scenario was converted into an intuitive network computing. Firstly

according to the drilling process

a complex network that includes 59 nodes and 102 edges was constructed to represent the accident scene and calculate the clustering coefficient. Secondly

referring to the Shannon entropy theory

the risk entropy was introduced to characterize the uncertainty of risk transmission

in view of its randomness and fuzziness. Finally

the shortest path formulation of the blowout network was described

and the formulation was then converted into a liner programming and a solution of the shortest path of every initial event was provided by utilizing the Dijkstra algorithm. The results show that the clustering coefficient of deepwater drilling blowout network is 0.132. The evolutional structure has the characteristics of small world with low aggregation but high evolutionary of nodes. In addition

shallow gas during drilling has the greatest influence on the blowout accident. The blowout accident has the greatest impact

but the risk of all initial events can be caused by a few steps to cause the blowout accident to verify the feasibility of the method in the quantitative risk assessment of complex process systems.

关键词

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references

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