摘要
随着大数据、人工智能等新兴信息技术的涌现,井下作业监督管理机构也开始探索作业监督模式的创新。基于大数据与人工智能的概念内涵及其在井下作业监督中应用的研究现状,从监督部门和采油井两个角度出发,以获取、处理、分析、应用和存储5个层级为基础,构建了大数据与人工智能双驱动的井下作业监督模式框架,精准对接作业方式与采油井作业需求,以推动井下作业数智化监督实现跨越式发展。
With the emergence of new information technologies such as big data and artificial intelligence,underground operation supervision and management institutions have also begun to explore innovations in operation supervision models.Based on the conceptual connotations of big data and artificial intelligence and the current research status of their application in underground operation supervision,from the two perspectives of supervision department and production well,based on the five levels of acquisition,processing,analysis,application and storage,an underground operation supervision mode framework driven by big data and artificial intelligence was constructed to accurately match the operation mode and production well operation needs,so as to promote the leapfroding development of downhole operation digital intelligence supervision.
作者
穆笛
MU Di(Research Institute of Technology,No.3 Oil Production Plant,PetroChina Daqing Oilfield Co.,Ltd.,Daqing,Heilongjiang 163113,China)
出处
《石油工业技术监督》
2025年第10期13-17,共5页
Technology Supervision in Petroleum Industry
关键词
大数据
人工智能
井下作业
监督管理
模式框架
big data
artificial intelligence
underground work/downhole operation
supervision
mode framework
