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

doi:10.11949/j.issn.0438-1157.20180501

化工学报 ›› 2019, Vol. 70 ›› Issue (1): 388-397.DOI: 10.11949/j.issn.0438-1157.20180501

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¹(),陈国明¹(),郑纯亮^1,²,吴翔飞¹,朱高庚¹

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

收稿日期:2018-05-14 修回日期:2018-06-21 出版日期:2019-01-05 发布日期:2019-01-05
通讯作者: 陈国明
作者简介:孟祥坤（1988—），男，博士研究生，<email>wsdy1002@163.com</email>|陈国明（1962—），男，博士，教授，<email>offshore@126.com</email>
基金资助:
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)

Risk evaluation model of deepwater drilling blowout accident based on risk entropy and complex network

Xiangkun MENG¹(),Guoming CHEN¹(),Chunliang ZHENG^1,²,Xiangfei WU¹,Gaogeng ZHU¹

1. Center for Offshore Engineering and Safety Technology, China University of Petroleum, Qingdao 266580, Shandong, China
2. Offshore Oil Engineering Qingdao Co., Ltd., Qingdao 266520, Shandong, China

Received:2018-05-14 Revised:2018-06-21 Online:2019-01-05 Published:2019-01-05
Contact: Guoming CHEN

摘要/Abstract

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。

关键词: 深水钻井井喷, 安全, 过程系统, 不确定性, 熵, 复杂网络, 最短路径

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.

Key words: deepwater drilling blowout, safety, process systems, uncertainty, entropy, complex network, shortest path

中图分类号:

TE 58

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.

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

图/表 8

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编号	风险因素	编号	风险因素	编号	风险因素
v₁	钻进操作因素	v₂₁	损坏固井质量	v₄₁	溢流进入隔水管
v₂	工艺因素	v₂₂	表层套管下沉	v₄₂	关闭环形BOP
v₃	自然因素	v₂₃	地层压力高于井底压力	v₄₃	环形BOP密封失效
v₄	设备因素	v₂₄	井底压力过大	v₄₄	环形BOP机械故障
v₅	固井质量差	v₂₅	压裂地层	v₄₅	液压系统故障
v₆	起钻过快	v₂₆	溢流	v₄₆	环形BOP操作失误
v₇	循环漏失	v₂₇	溢流流体进入井筒环空	v₄₇	环形BOP关闭失败
v₈	抽汲压力过大	v₂₈	早期溢流监测失效	v₄₈	关闭闸板BOP
v₉	钻井液密度过低	v₂₉	钻井液流量指示器失效	v₄₉	剪切闸板密封失效
v₁₀	气侵钻井液	v₃₀	气体流量传感器失效	v₅₀	闸板BOP机械故障
v₁₁	钻井液密度过大	v₃₁	随钻测压工具失效	v₅₁	闸板BOP操作失误
v₁₂	钻遇高渗地层	v₃₂	气体含量传感器失效	v₅₂	水合物阻塞BOP组
v₁₃	钻遇浅层气	v₃₃	控制电路失效	v₅₃	自动关断失效
v₁₄	钻遇浅层水流	v₃₄	钻井监督显示器故障	v₅₄	RCD密封失效
v₁₅	套管破裂	v₃₅	录井工对泥浆池增量判断失误	v₅₅	分流系统机械故障
v₁₆	钻杆失效	v₃₆	司钻与录井工协作失误	v₅₆	RCD操作失误
v₁₇	隔水管系统失效	v₃₇	误报警导致司钻判断失误	v₅₇	不压井起下作业装置失效
v₁₈	泥浆泵失效	v₃₈	未监测到井涌	v₅₈	分流失效
v₁₉	井口系统失效	v₃₉	井涌判断失误	v₅₉	井喷
v₂₀	动力故障	v₄₀	井涌后未停钻	—	—

编号	风险因素	编号	风险因素	编号	风险因素
v₁	钻进操作因素	v₂₁	损坏固井质量	v₄₁	溢流进入隔水管
v₂	工艺因素	v₂₂	表层套管下沉	v₄₂	关闭环形BOP
v₃	自然因素	v₂₃	地层压力高于井底压力	v₄₃	环形BOP密封失效
v₄	设备因素	v₂₄	井底压力过大	v₄₄	环形BOP机械故障
v₅	固井质量差	v₂₅	压裂地层	v₄₅	液压系统故障
v₆	起钻过快	v₂₆	溢流	v₄₆	环形BOP操作失误
v₇	循环漏失	v₂₇	溢流流体进入井筒环空	v₄₇	环形BOP关闭失败
v₈	抽汲压力过大	v₂₈	早期溢流监测失效	v₄₈	关闭闸板BOP
v₉	钻井液密度过低	v₂₉	钻井液流量指示器失效	v₄₉	剪切闸板密封失效
v₁₀	气侵钻井液	v₃₀	气体流量传感器失效	v₅₀	闸板BOP机械故障
v₁₁	钻井液密度过大	v₃₁	随钻测压工具失效	v₅₁	闸板BOP操作失误
v₁₂	钻遇高渗地层	v₃₂	气体含量传感器失效	v₅₂	水合物阻塞BOP组
v₁₃	钻遇浅层气	v₃₃	控制电路失效	v₅₃	自动关断失效
v₁₄	钻遇浅层水流	v₃₄	钻井监督显示器故障	v₅₄	RCD密封失效
v₁₅	套管破裂	v₃₅	录井工对泥浆池增量判断失误	v₅₅	分流系统机械故障
v₁₆	钻杆失效	v₃₆	司钻与录井工协作失误	v₅₆	RCD操作失误
v₁₇	隔水管系统失效	v₃₇	误报警导致司钻判断失误	v₅₇	不压井起下作业装置失效
v₁₈	泥浆泵失效	v₃₈	未监测到井涌	v₅₈	分流失效
v₁₉	井口系统失效	v₃₉	井涌判断失误	v₅₉	井喷
v₂₀	动力故障	v₄₀	井涌后未停钻	—	—

语言变量	梯形模糊数	定性描述	概率表征
非常低(VL)	(0, 0, 0.1, 0.2)	基本不可能发生	(0, 10^-6)
低(L)	(0.1, 0.25, 0.25, 0.4)	全寿命周期内可能发生	(10^-6, 10^-3)
中等(M)	(0.3, 0.5, 0.5, 0.7)	全寿命周期内有时发生	(10^-3, 10^-2)
高(H)	(0.6, 0.75, 0.75, 0.9)	全寿命周期内发生数次	(10^-2, 10^-1)
非常高(VH)	(0.8, 0.9, 1, 1)	经常会发生	(10^-1, 1)

语言变量	梯形模糊数	定性描述	概率表征
非常低(VL)	(0, 0, 0.1, 0.2)	基本不可能发生	(0, 10^-6)
低(L)	(0.1, 0.25, 0.25, 0.4)	全寿命周期内可能发生	(10^-6, 10^-3)
中等(M)	(0.3, 0.5, 0.5, 0.7)	全寿命周期内有时发生	(10^-3, 10^-2)
高(H)	(0.6, 0.75, 0.75, 0.9)	全寿命周期内发生数次	(10^-2, 10^-1)
非常高(VH)	(0.8, 0.9, 1, 1)	经常会发生	(10^-1, 1)

Parameter	Value
S_ij(E_i, E_j)	(1, 0.825, 0.825)
AA(E_i)	(0.913, 0.913, 0.825)
RA(E_i)	(0.344,0.344, 0.311)
CC(E_i)	(0.402, 0.369, 0.229)
R_AG	(0.646, 0.784, 0.807, 0.923)

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

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Edge	Direction	Probability	Entropy	Edge	Direction	Probability	Entropy	Edge	Direction	Probability	Entropy
e₁	v₁~v₅	1.00×10^-3	6.91	e₃₅	v₂₁~v₅	8.02×10^-1	0.22	e₆₉	v₄₂~v₄₄	1.00×10^-3	6.91
e₂	v₁~v₆	4.84×10^-2	3.03	e₃₆	v₂₁~v₇	2.07×10^-1	1.58	e₇₀	v₄₂~v₄₅	5.25×10^-4	7.55
e₃	v₂~v₉	5.00×10^-2	3.00	e₃₇	v₂₂~v₇	8.22×10^-2	2.50	e₇₁	v₄₂~v₄₆	4.35×10^-3	3.14
e₄	v₂~v₁₀	3.00×10^-5	10.41	e₃₈	v₂₃~v₂₆	0.99	0.01	e₇₂	v₄₃~v₄₇	0.99	0.01
e₅	v₂~v₁₁	5.00×10^-2	3.00	e₃₉	v₂₄~v₂₅	8.00×10^-1	0.22	e₇₃	v₄₄~v₄₃	2.12×10^-2	3.85
e₆	v₃~v₁₂	1.50×10^-1	1.90	e₄₀	v₂₅~v₂₃	7.35×10^-1	0.31	e₇₄	v₄₄~v₄₅	9.02×10^-3	4.71
e₇	v₃~v₁₃	2.69×10^-1	1.31	e₄₁	v₂₅~v₂₆	0.99	0.01	e₇₅	v₄₄~v₄₇	0.99	0.01
e₈	v₃~v₁₄	4.00×10^-5	10.13	e₄₂	v₂₆~v₂₇	0.99	0.01	e₇₆	v₄₅~v₄₇	0.99	0.01
e₉	v₄~v₁₅	6.40×10^-4	7.35	e₄₃	v₂₇~v₂₈	2.07×10^-1	1.58	e₇₇	v₄₆~v₄₅	1.00×10^-3	6.91
e₁₀	v₄~v₁₆	5.00×10^-4	7.60	e₄₄	v₂₇~v₂₉	1.10×10^-4	9.12	e₇₈	v₄₆~v₄₇	0.99	0.01
e₁₁	v₄~v₁₇	5.10×10^-4	7.58	e₄₅	v₂₇~v₃₀	1.10×10^-4	9.12	e₇₉	v₄₇~v₄₈	0.99	0.01
e₁₂	v₄~v₁₈	1.60×10^-3	6.44	e₄₆	v₂₇~v₃₁	3.00×10^-3	5.81	e₈₀	v₄₈~v₄₉	3.55×10^-2	3.34
e₁₃	v₄~v₁₉	2.00×10^-3	6.21	e₄₇	v₂₇~v₃₂	1.10×10^-3	6.81	e₈₁	v₄₈~v₅₀	1.00×10^-3	6.91
e₁₄	v₄~v₂₀	6.25×10^-4	7.38	e₄₈	v₂₇~v₃₃	1.00×10^-4	9.21	e₈₂	v₄₈~v₅₁	6.00×10^-4	7.42
e₁₅	v₅~v₇	2.70×10^-2	3.61	e₄₉	v₂₇~v₃₄	1.10×10^-4	9.12	e₈₃	v₄₈~v₅₂	4.22×10^-3	5.47
e₁₆	v₆~v₈	5.40×10^-1	0.62	e₅₀	v₂₇~v₃₅	1.00×10^-3	6.91	e₈₄	v₄₉~v₅₃	0.99	0.01
e₁₇	v₇~v₂₃	9.00×10^-1	0.11	e₅₁	v₂₇~v₃₆	1.00×10^-3	6.91	e₈₅	v₅₀~v₄₉	2.85×10^-2	3.56
e₁₈	v₈~v₇	8.57×10^-2	2.46	e₅₂	v₂₇~v₃₇	1.00×10^-3	6.91	e₈₆	v₅₀~v₅₃	0.99	0.01
e₁₉	v₈~v₂₃	9.20×10^-1	0.08	e₅₃	v₂₈~v₃₈	0.99	0.01	e₈₇	v₅₁~v₅₀	1.25×10^-1	2.08
e₂₀	v₉~v₂₃	9.10×10^-1	0.09	e₅₄	v₂₉~v₃₈	0.99	0.01	e₈₈	v₅₁~v₅₂	4.25×10^-1	0.86
e₂₁	v₁₀~v₉	6.70×10^-1	0.40	e₅₅	v₃₀~v₃₈	0.99	0.01	e₈₉	v₅₁~v₅₃	0.99	0.01
e₂₂	v₁₀~v₂₃	8.00×10^-1	0.22	e₅₆	v₃₁~v₃₈	0.99	0.01	e₉₀	v₅₂~v₅₃	0.99	0.01
e₂₃	v₁₁~v₂₄	8.90×10^-1	0.12	e₅₇	v₃₂~v₃₈	0.99	0.01	e₉₁	v₅₃~v₅₄	1.00×10^-3	6.91
e₂₄	v₁₂~v₂₅	8.20×10^-2	0.20	e₅₈	v₃₃~v₃₈	0.99	0.01	e₉₂	v₅₃~v₅₅	3.60×10^-3	5.63
e₂₅	v₁₃~v₂₆	0.99	0.01	e₅₉	v₃₄~v₃₈	0.99	0.01	e₉₃	v₅₃~v₅₆	4.30×10^-3	5.45
e₂₆	v₁₄~v₂₁	1.50×10^-1	1.90	e₆₀	v₃₅~v₃₆	8.56×10^-2	2.46	e₉₄	v₅₃~v₅₇	4.30×10^-3	5.45
e₂₇	v₁₄~v₂₂	2.00×10^-1	1.61	e₆₁	v₃₅~v₃₉	0.99	0.01	e₉₅	v₅₄~v₅₈	0.99	0.01
e₂₈	v₁₅~v₂₆	0.99	0.01	e₆₂	v₃₆~v₃₉	0.99	0.01	e₉₆	v₅₅~v₅₄	3.85×10^-1	0.95
e₂₉	v₁₆~v₂₆	0.99	0.01	e₆₃	v₃₇~v₃₉	0.99	0.01	e₉₇	v₅₅~v₅₈	0.99	0.01
e₃₀	v₁₇~v₂₆	0.99	0.01	e₆₄	v₃₈~v₄₀	7.00×10^-1	0.36	e₉₈	v₅₆~v₅₅	8.55×10^-2	2.46
e₃₁	v₁₈~v₂₆	0.99	0.01	e₆₅	v₃₉~v₄₀	3.00×10^-1	1.20	e₉₉	v₅₆~v₅₇	3.40×10^-2	3.38
e₃₂	v₁₉~v₂₆	0.99	0.01	e₆₆	v₄₀~v₄₁	0.99	0.01	e₁₀₀	v₅₆~v₅₈	0.99	0.01
e₃₃	v₂₀~v₁₈	2.15×10^-1	1.54	e₆₇	v₄₁~v₄₂	0.99	0.01	e₁₀₁	v₅₇~v₅₈	0.99	0.01
e₃₄	v₂₀~v₂₆	0.99	0.01	e₆₈	v₄₂~v₄₃	7.00×10^-2	2.66	e₁₀₂	v₅₈~v₅₉	0.99	0.01

Initial event	Shortest path	Risk entropy	Probability
v₁	v₁→v₆→v₈→v₂₃→v₂₈→v₄₃→v₄₉→v₅₆→v₅₉	17.11	3.32×10^-8
v₂	v₂→v₉→v₂₃→v₂₈→v₄₃→v₄₉→v₅₆→v₅₉	16.58	6.30×10^-8
v₃	v₃→v₁₃→v₂₈→v₃₈→v₄₃→v₄₉→v₅₆→v₅₉	14.80	3.73×10^-7
v₄	v₄→v₁₉→v₂₈→v₃₈→v₄₃→v₄₉→v₅₆→v₅₉	19.70	2.78×10^-9

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