石油化工安全环保技术 ›› 2025, Vol. 41 ›› Issue (3): 13-16.

• 安全与环保管理 • 上一篇    

安全指标在海洋石油开发安全管理中的应用与实践

靳亚军 张晓辉 杨玉红   

  1. 中海油田服务股份有限公司,河北 廊坊 005201
  • 收稿日期:2025-04-25 接受日期:2025-05-15 出版日期:2025-06-20 发布日期:2025-07-09
  • 作者简介:靳亚军,男, 2011 年毕业于重庆科技大学石油工程专业,现在中海油田服务股份有限公司从事安全管理工作,工程师。电话: 15122226267, E-mail: jinyj@cosl.com.cn

Application and Practice of Safety Indicators in Safety Management of Offshore Oil Development

Jin Yajun, Zhang Xiaohui, Yang Yuhong   

  1. China Oilfield Services Limited, Langfang, Hebei, 005201
  • Received:2025-04-25 Accepted:2025-05-15 Online:2025-06-20 Published:2025-07-09

摘要: 海洋石油开发作为高危行业,其安全治理需构建量化评估体系。以中海油田服务股份有限公司为研究对象,基于海因里希法则与瑞士奶酪模型理论框架,创新性提出“双维度安全指标体系”(通用指标 + 特性化指标),构建覆盖作业全周期的风险预警系统。通过引入班组固定率、风险转化效能系数等 12 项量化指标,实现风险感知精准度提升 47%。实证研究表明,该体系使重复隐患发生率下降 62%, OSHA 可记录事件率低于行业均值 35%,形成“指标驱动 - 文化渗透 - 行为矫正”的闭环管理范式。研究成果可为高复杂度工业场景的安全治理提供方法论参考。

关键词: 安全指标体系, 风险预警模型, 风险管控, 安全生产形势研判, 安全干预文化

Abstract: As a high-risk industry, offshore oil development requires the establishment of a quantitative assessment system for safety governance. Taking China Oilfield Services Limited (COSL) as the research subject, this study innovatively proposes a "dual-dimensional safety indicator system" (generic indicators + specific indicators) based on Heinrich's Law and the Swiss Cheese Model theoretical framework. It has developed a risk early-warning system covering the entire operational lifecycle. By introducing 12 quantitative indicators such as Crew Stability Rate and Risk Conversion Efficiency Coefficient, the risk perception accuracy has been improved by 47%. Empirical studies demonstrate that this system achieved a 62% reduction in recurring hazard incidence and maintained the OSHA recordable incident rate 35% below the industry average, establishing a closed-loop management paradigm of "indicator-driven process, cultural permeation, and behavioral correction". The research outcomes provide methodological reference for safety governance in highly complex industrial scenarios.

Key words: safety indicator system, risk early-warning model, risk control and management, work safety situation assessment, safety intervention culture