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大数据分析在油气田资产设备管理中的应用

Application of Big Data Analysis on Assets and Equipment Management in Oil&Gas Field
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摘要 大数据分析应用可提升油田企业的核心竞争力。基于目前油田企业设备管理现有问题,中国石油工程建设有限公司(CPECC)提出了一整套油田企业资产设备完整性管理的信息化实施方案,包括开发了获国家发明专利的基于大数据算法的机泵选型及分析技术,研发了位列国际前沿的油气田数字化平台。该方案是以自动化技术、通信技术为基础,结合先进信息技术,面向油田企业资产设备运营管理需求,预测评判精度高,推广前景广阔,对油田企业的资产设备管理、信息化管理、生产实际问题解决、安全高效生产等具有很重要的意义。 The application of big data analysis can enhance the core competitiveness of oilfield enterprises.Based on the current problems in equipment management of oilfield enterprises,China Petroleum Engineering&Construction Co.,Ltd.(CPECC)has put forward a complete set of informatization implementation scheme for asset and equipment integrity management of oilfield enterprises,including the development of machine pump selection and analysis technology based on big data algorithm,which has won the national invention patent,and the development of an international cutting-edge oil and gas field digital platform.The scheme is based on automation technology and communication technology,combined with advanced information technology,and is oriented to the operation and management needs of oilfield enterprise assets and equipment.The prediction and evaluation accuracy is high,and the promotion prospect is broad.It is of great significance to the asset and equipment management,information management,production problem solving,safe and efficient production of oilfield enterprises.
作者 王煜彤 周靖伟 王维 喻炫耀 WANG Yutong;ZHOU Jingwei;WANG Wei;YU Xuanyao(Administrative Affairs Department,China Petroleum Engineering&Construction Corporation(CPECC),Beijing,100011 China;Process Department of Beijing Design Branch,China Petroleum Engineering&Construction Corp.(CPECC),Beijing,100085 China;Middle East Branch,China Petroleum Engineering&Construction Corporation(CPECC),Beijing,100011 China;College of Mechanical and Transportation Engineering,China University of Petroleum,Beijing,102249 China)
出处 《科技创新导报》 2022年第15期131-135,共5页 Science and Technology Innovation Herald
关键词 大数据 智能学习 最小二乘支持向量机 数字化平台 信息化 Big data Intelligence learning LSSVM Digital platform Information
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