油气管网行业大模型的思考及应用探索  

Reflections and application exploration of large models for the oil and gas pipeline network industry

作　　者：宫敬[1] 吴冕 赵周丙 宋尚飞 戈志伟 虞维超 GONG Jing;WU Mian;ZHAO Zhoubing;SONG Shangfei;GE Zhiwei;YU Weichao(College of Mechanical and Transportation Engineering,China University of Petroleum(Beijing)//National Engineering Research Center for Pipeline Safety//Beijing Key Laboratory of Urban Oil and Gas Distribution Technology//MOE Key Laboratory of Petroleum Engineering;PipeChina Digital Co.,Ltd.;PipeChina Oil&Gas Control Center)

机构地区：[1]中国石油大学(北京)机械与储运工程学院•油气管道输送安全国家工程研究中心•城市燃气输配技术北京市重点实验室•石油工程教育部重点实验室 [2]北京智网数科技术有限公司 [3]国家管网集团油气调控中心

出　　处：《油气储运》2025年第4期379-393,共15页Oil & Gas Storage and Transportation

基　　金：国家自然科学基金资助项目“含蜡原油常温输送机理及流动改性方法研究”,51534007;国家自然科学基金青年基金资助项目“裹挟粉砂的水基流动体系中CO_(2)-CH_(4)水合物分解动力学机制”,52104069;北京市自然基金面上项目“深水油气混输管道中赋存蜡的水合物颗粒黏聚/黏附作用机制研究”,3232030;中国石油大学(北京)科研基金资助项目“天然气水合物开发过程中水合物分解动力学机理研究”,2462023BJRC018;中国石油大学(北京)科研基金资助项目“基于大数据的天然气管网智能运行与控制研究”,2462020YXZZ045。

摘　　要：【目的】随着人工智能技术的飞速发展,大模型技术在众多领域得到广泛应用,展现出巨大潜力。油气管网作为国家能源输送的关键基础设施,其智能化升级对保障能源安全、提升运行效率具有战略意义。当前,大模型技术在油气管网领域的应用尚处于探索阶段,面临技术融合深度不足、行业适配性难及工程化应用瓶颈等挑战。大力深入推动大模型技术与油气管网行业的融合,成为突破传统智能化瓶颈、实现管网系统智慧化转型的关键路径。【方法】从数据、算力、算法、研究模式4个关键维度出发,深入剖析了现有大模型在油气管网行业应用中面临的研究难点。在此基础上,基于智能油气管网系统建设与油气管网行业大模型建设的双重视角,提出了涵盖基础设施层、技术基座层、模型与应用层、控制层的油气管网行业大模型体系架构。依托该架构,针对性地为油气管网行业大模型建设过程中的难题提供了解决方案,并制定了完整的技术路线。【结果】多层级构建的油气管网行业大模型体系架构,为油气管网智能化系统的建设、运行以及大模型的研发,提供了系统的技术支撑。基于架构提出的数据集构建方法、一体化平台、多技术融合技术路线以及大模型分层构建的解决方案,有效解决了研究过程中在以上4个维度所遇到的难题。将新制定的解决方案应用于天然气管网智能调控、天然气需求预测等场景,显著提升了相关领域的智能化水平。【结论】研究成果为油气管网行业的智能化升级提供了全面的技术指导,对提升智能管网的认知水平、推动行业大模型的建设具有重要意义。未来,大模型在油气管网行业的应用将朝着全面化、深层次方向拓展,持续紧跟先进技术发展步伐、高度重视数据资产建设、大力推动技术融合,是提升油气管网行业智能化水平的�Objective With the rapid development of artificial intelligence(AI),large model technology has been widely applied and has demonstrated significant potential across various fields.Given that oil and gas pipeline networks are key infrastructure for national energy transportation,the potential application of large model technology in their intelligent upgrading process has garnered increasing attention.However,numerous challenges within this field have hindered deeper applications.Therefore,further promoting the fusion of large model technology with the oil and gas pipeline network industry is considered an important task for enhancing the intelligence level of this industry.Methods This paper presents the challenges encountered in the existing applications of large models within the oil and gas pipeline network industry,through an in-depth analysis that examines four key dimensions:data,computing power,algorithms,and research paradigms.Based on the analysis results,a large model architecture for the oil and gas pipeline network industry is proposed,focusing on two aspects:the construction of intelligent oil and gas pipeline network systems and the development of large models specifically applicable to this industry.This architecture consists of the infrastructure layer,technical foundation layer,model and application layer,and control layer.Building on the proposed architecture,targeted solutions are presented to address the challenges associated with the development of large models for the industry,along with the formulation of a complete technical roadmap.Results The large model architecture established for the oil and gas pipeline network industry from multiple dimensions provides systematic technical support for the construction and operation of intelligent systems for oil and gas pipeline networks and the research and development of associated large models.The dataset construction methodology,integrated platform,multi-technology fusion technical roadmap,and layered construction solution for large models propo

关 键 词：油气管网 行业大模型 大模型架构 多技术融合 

分 类 号：TE832[石油与天然气工程—油气储运工程]