摘要
针对传统机采井生产管理模式效率低、人员成本高等问题,国内油田相继开展了数字化油田建设,形成了机采井自动监测、诊断和优化控制技术,满足了机采井高效自动运行的需要,但依旧存在诊断精度低、智能化有待提高等问题。国外油气大公司智能采油方面处于国际领先地位,重点建设成果有智能抽油机、远程智能监测优化系统、人工智能技术应用等,实现了生产数据实时监测、平台诊断分析、故障预警报警、潜力方案设计等功能。借助于大数据技术、物联网技术和人工智能技术的快速发展,未来机采井将向着平台井智能群控、基于边缘计算的机采井本地闭环调控和生产数据智能挖掘方向发展。借鉴国外油气公司智能采油实践,开展数字孪生、大数据挖潜等人工智能技术的研究和应用,推进"数字油田"向"智能采油"转变,大力提高油井生产和管理效率。
In order to solve the problems of low efficiency and high personnel cost in the traditional production management mode of the mechanical recovery wells,digital construction is carried out in the oilfields in China successively and automatic monitoring,diagnosis and optimization control technologies are formed to meet the needs of efficient automatic running of the mechanical recovery wells,but there are still problems such as low diagnostic accuracy and intelligence to be improved.Foreign oil and gas companies are in the international leading position in intelligent oil recovery,whose key achievements include intelligent pumping machines,remote intelligent monitoring and optimization systems,and artificial intelligence technology applications and so on.And then real-time monitoring of production data,platform diagnosis and analysis,fault warning and alarm,and potential program design may be realized.With the rapid technology development of big data,internet of things and artificial intelligence,the machine recovery wells will develop toward intelligent group control of platform wells,local closed-loop regulation and control of the mechanical recovery wells based on edge computing and intelligent mining of production data in the future.Drawing on the practices of intelligent oil production in foreign oil and gas companies,digital twin and big data mining and other artificial intelligence technologies should be researched and applied to promoting the transformation of"digital oil-field"to"intelligent oil production",and the production and management efficiency of oil wells may be improved greatly.
作者
张凯波
Zhang Kaibo(Oil Production Engineering Research Institute of Daqing Oilfield Co.,Ltd.,Daqing Heilongjiang 163453;Heilongjiang Provincial Key Laboratory of Oil and Gas Reservoir Stimulation,Daqing Heilongjiang 163453)
出处
《中外能源》
CAS
2021年第9期45-51,共7页
Sino-Global Energy
关键词
机采井
物联网
智能采油技术现状
优化控制
人工智能
mechanical recovery wells
internet of things
status quo of intelligent oil production technology
optimization and controlling
artificial intelligence
