油气长输管道事故致因模型构建与要素分析

doi:10.16265/j.cnki.issn1003-3033.2025.12.0535

摘要/Abstract

摘要：

为探究油气管道事故系统致因模型的理论内涵和实践路径,首先,统计241起国内外油气长输管道事故,对比分析国内外事故原因类型和调查报告内容;其次,融合人因分析与分类系统(HFACS)模型的因素体系和系统理论事故建模与过程(STAMP)模型的层级结构,提出涵盖4个系统层级和17个影响因素的事故致因模型;最后,运用N-K模型和社会网络分析方法开展风险耦合度计算、网络模型构建、中心性分析和核心-边缘分析。结果表明:设备故障和管道腐蚀占油气长输管道事故原因的35.3%和22.8%;风险耦合值与系统层级耦合数量成正比;安全培训不足、应急响应延迟、安全监督缺失、风险意识不足、风险沟通缺失、行为违规、设备工艺问题是事故的核心影响因素,事故全生命周期管理包括缩减阶段、预备阶段、反应阶段和恢复阶段。

关键词: 油气长输管道事故, 事故致因模型, 事故影响因素, 系统理论事故建模与过程(STAMP), 人因分析与分类系统(HFACS), N-K模型, 社会网络分析

Abstract:

In order to explore the theoretical connotation and practical path of the systematic causation model of oil and gas pipeline accidents, 241 domestic and international oil and gas long-distance pipeline accidents were counted first, and the types of domestic and foreign accident causes and the contents of investigation reports were compared and analyzed. Secondly, we integrated the factor system of HFACS model and the hierarchical structure of STAMP model, and put forward an accident causation model that covers 4 system levels and 17 influencing factors. Finally, the N-K model and social network analysis method were used to carry out risk coupling calculation, network model construction, centrality analysis and core-edge analysis. The results show that equipment failure and pipeline corrosion account for 35.3% and 22.8% of the causes of oil and gas long-distance pipeline accidents. The risk coupling value is directly proportional to the number of system-level couplings. Inadequate safety training, delayed emergency response, lack of safety oversight, lack of risk awareness, lack of risk communication, behavioral violations and equipment process issues are the core influences on the accidents. The full life cycle management of accidents includes the reduction phase, readiness phase, response phase, and recovery phase.

Key words: oil and gas long-distance pipeline accidents, accident causation model, accident influencing factors, systems theoretic accident modeling and processes(STAMP), human factors analysis and classification system(HFACS), N-K model, social network analysis

中图分类号:

X937

王乾, 常维纯, 赵晶荣, 王智浩, 苟泽念, 佟瑞鹏. 油气长输管道事故致因模型构建与要素分析[J]. 中国安全科学学报, 2025, 35(12): 111-118.

WANG Qian, CHANG Weichun, ZHAO Jingrong, WANG Zhihao, GOU Zenian, TONG Ruipeng. Construction and factor analysis of accident causation model for long-distance oil and gas pipelines[J]. China Safety Science Journal, 2025, 35(12): 111-118.

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调查报告内容	中国	美国	加拿大
事故基本信息	√	√	√
事故经过与应急处理	√	√	√
事故损失评估	√	√	√
技术调查与实验分析	—	√	√
管道完整性管理	—	√	√
事故原因分析	√	√	√
监管体系与责任追究	√	—	—
防范措施与改进建议	√	—	√
附录(调查数据)	—	√	—

系统层次	控制结构	影响因素	频数	占比/%
政府层 (24)	监督职能	应急管理不当	10	12.99
政府层 (24)	监督职能	监管责任模糊	16	20.78
企业层 (71)	组织影响	安全培训不足	21	27.27
	组织影响	应急响应延迟	27	35.06
	安全监督	安全监督违规	11	14.29
		安全监督缺失	53	68.83
		项目管理问题	17	22.08
	第三方因素	施工破坏	11	14.29
	第三方因素	蓄意破坏	3	3.90
行为层 (68)	人员状态	风险意识不足	36	46.75
		风险沟通缺失	25	32.47
		知识技能不良	16	20.78
	人员行为	行为失误	15	19.48
	人员行为	行为违规	32	41.56
物理层 (56)	自然灾害	地质灾害/ 极端气候	9	11.69
	管道腐蚀	内腐蚀/外腐蚀/应力腐蚀	12	15.58
	设备工艺	焊缝缺陷/ 设计问题	39	50.65

耦合类型	事件	频数	频率
单因素风险耦合	0010	1	0.013 0
双因素风险耦合	0110	15	0.194 8
	0101	3	0.039 0
	0011	4	0.051 9
	1100	1	0.013 0
多因素风险耦合	0111	30	0.389 6
	1011	1	0.013 0
	1101	5	0.064 9
	1110	4	0.051 9
	1111	13	0.168 8

因素耦合	耦合值	排序
T₄ (a,b,c,d)	0.107 1	1
T₃₁ (a,c,d)	0.080 5	2
T₃₂ (a,b,c)	0.069 6	3
T₂₁ (a,c)	0.051 6	4
T₃₃ (b,c,d)	0.034 9	5
T₃₄ (a,b,d)	0.023 4	6
T₂₂ (c,d)	0.014 8	7
T₂₃ (b,c)	0.014 7	8
T₂₄ (a,d)	0.007 2	9
T₂₅ (a,b)	0.006 8	10
T₂₆ (b,d)	0.003 9	11

影响因素	度中心性	接近中心性	中介中心性
E4	195	16	2.07
P3	150	16	2.07
B1	142	16	2.07
B5	130	16	2.07
E2	122	16	2.07
B2	110	17	0.78
E1	101	16	2.07
B3	84	17	0.78
E5	75	18	0.27
B4	69	18	0.27
G2	68	18	0.4
E3	50	19	0
P2	49	19	0
G1	41	16	2.07
E6	34	21	0
P1	28	22	0
E7	10	25	0