数据驱动背景下的油气管道风险评价挑战  

Data-driven:challenges in pipeline risk assessment for oil and gas

作　　者：程可心 杨玉锋 李守宝 郑文培[2] 张强 石建成 CHENG Kexin;YANG Yufeng;LI Shoubao;ZHENG Wenpei;ZHANG Qiang;SHI Jiancheng(PipeChina Science&Technology Research Instituter;College of Safety and Ocean Engineering,China University of Petroleum(Beijing))

机构地区：[1]国家管网集团科学技术研究总院分公司,天津市300457 [2]中国石油大学(北京)安全与海洋工程学院

出　　处：《管道保护》2025年第1期88-96,共9页

基　　金：国家应急管理部重点科技计划资助项目“油气管网系统环境安全重大风险防控关键技术研究”(2024EMST090903);国家管网集团科技资助项目“基于多源数据的管道风险评价深化研究”(AQWH202302)。

摘　　要：随着油气管道建设规模不断扩大以及运营环境日益复杂,传统的风险评价方法逐渐暴露出其局限性,难以满足现代管道安全管理对精确度、实时性和适应性的需求。为了实现风险的高效预警,通过深入分析数据驱动的风险评价方法在油气管道领域的发展与应用,指出了当前技术应用中的优势、挑战与发展方向。研究表明:基于数据驱动的模型在管道风险评估中表现出更强的适应性和准确性,能够提供更为细致和实时的风险预警。然而,数据驱动方法比较依赖于大量高质量的数据,容易出现过拟合问题,且由于模型的“黑箱”特性使其解释性较差,对制定安全关键决策产生不利的影响。本文提出的发展建议可为数据驱动背景下的油气管道风险管理提供全新的视角和解决方案。With the continuous expansion of oil and gas pipeline construction and the increasing complexity of operational environments,traditional risk assessment methods have gradually become limited,thus failing to satisfy the demands for accuracy,timeliness,and adaptability in modern pipeline safety management.To achieve efficient early risk warning,this paper comprehensively analyzed the development and application of data-driven risk assessment methods,summarizing the advantages,challenges,and future directions of current technological applications.The study found that data-driven models exhibit stronger adaptability and accuracy in pipeline risk assessment,allowing more detailed and real-time risk warnings.However,these methods rely highly on large volumes of high-quality data and are prone to overfitting.Moreover,the“black-box”nature of the models causes poor interpretability,bringing challenges for making critical safety-related decisions.This paper proposes several development suggestions to address the issues and challenges faced by intelligent pipeline networks in terms of both safety and economic operation.

关 键 词：油气管道 数据驱动 机器学习 风险评价 风险管理 

分 类 号：TE88[石油与天然气工程—油气储运工程]