基于边缘计算的物网技术在智能油气田中的应用研究  

作　　者：叶康林 肖逸军 郑骏伟 范志弘 康璐 

机构地区：[1]中国石油西南油气田公司通信与信息技术中心,四川成都610051

出　　处：《工业控制计算机》2022年第2期35-36,38,共3页Industrial Control Computer

摘　　要：在工业物联网(IIoT,Industrial Internet of Things)环境中部署机器学习已成为石油和天然气行业研究最多的课题之一。提出了一种基于边缘计算的智能油气田物联网系统,该系统以边缘计算的机器学习模型为核心,结合智能RTU的采集传输数据,两者相互补充利用。通过卡尔曼滤波器(KF, Kalman Filter)实现对数据的异常值侦测,利用边缘计算对数据安全分析进行了对策研究,完成油气生产的动态在线监测和控制,有效提高油气生产管理的智能化水平,满足智能化气田井场的远程监控要求。The deployment of machine learning in the industrial Internet of Things environment has become one of the most researched topics in the oil and gas industry.This paper proposes an intelligent oil and gas field Internet of Things system based on edge computing.The system takes the machine learning model of edge computing as the core and combines the collection and transmission data of intelligent RTU,and the two complement each other.The Kalman filter is used to realize the detection of data outliers,and the edge computing is used to conduct countermeasures for data security analysis.The dynamic online monitoring and control of oil and gas production is completed,which effectively improves the intelligent level of oil and gas production management and meets the needs of intelligent gas production.The remote monitoring requirements of the field well site.

关 键 词：物联网 边缘计算 智能RTU 卡尔曼滤波器 

分 类 号：TE4[石油与天然气工程—油气田开发工程] TN929.5[电子电信—通信与信息系统] TP391.44[电子电信—信息与通信工程]