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Intelligent Drilling and Completion:A Review

Intelligent Drilling and Completion:A Review

作     者:Gensheng Li Xianzhi Song Shouceng Tian Zhaopeng Zhu Gensheng Li;Xianzhi Song;Shouceng Tian;Zhaopeng Zhu

作者机构:State Key Laboratory of Petroleum Resources and ProspectingChina University of PetroleumBeijing 102249China 

出 版 物:《Engineering》 (工程(英文))

年 卷 期:2022年第18卷第11期

页      面:33-48页

核心收录:

学科分类:12[管理学] 0808[工学-电气工程] 08[工学] 0820[工学-石油与天然气工程] 0810[工学-信息与通信工程] 082001[工学-油气井工程] 0830[工学-环境科学与工程(可授工学、理学、农学学位)] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 0817[工学-化学工程与技术] 081104[工学-模式识别与智能系统] 0807[工学-动力工程及工程热物理] 0805[工学-材料科学与工程(可授工学、理学学位)] 0703[理学-化学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术(可授工学、理学学位)] 

基  金:support of the National Key Research and Development Project of China(2019YFA0708300) National Science Fund for Distinguished Young Scholars of China(52125401) National Natural Science Foundation of China(L1924060) 

主  题:Intelligent drilling and completion Artificial intelligence Intelligent application scenarios Literature review Systematic discuss 

摘      要:The application of artificial intelligence(AI)has become inevitable in the petroleum *** drilling and completion engineering,AI is regarded as a transformative technology that can lower costs and significantly improve drilling efficiency(DE),In recent years,numerous studies have focused on intelligent algorithms and their *** technologies,such as digital twins and physics-guided neural networks,are expected to play roles in drilling and completion ***,many challenges remain to be addressed,such as the automatic processing of multi-source and multi-scale ***,in intelligent drilling and completion,methods for the fusion of data-driven and physicsbased models,few-sample learning,uncertainty modeling,and the interpretability and transferability of intelligent algorithms are research *** on intelligent application scenarios,this study comprehensively reviews the research status of intelligent drilling and completion and discusses key research areas in the *** study aims to enhance the berthing of AI techniques in drilling and completion engineering.

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