Artificial intelligence:New age of transformation in petroleum upstream

作     者：Parth Solanki Dhruv Baldaniya Dhruvikkumar Jogani Bhavesh Chaudhary Manan Shah Ameya Kshirsagar Parth Solanki;Dhruv Baldaniya;Dhruvikkumar Jogani;Bhavesh Chaudhary;Manan Shah;Ameya Kshirsagar

作者机构：School of Petroleum TechnologyPandit Deendayal Petroleum UniversityGandhinagar382007GujaratIndia Department of Chemical EngineeringSchool of TechnologyPandit Deendayal Petroleum UniversityGandhinagar382007GujaratIndia Department of Information TechnologySymbiosis Institute of TechnologyPuneMaharashtraIndia 

出 版 物：《Petroleum Research》 (石油研究（英文）)

年 卷 期：2022年第7卷第1期

页      面：106-114页

核心收录：

学科分类：0202[经济学-应用经济学] 02[经济学] 0709[理学-地质学] 0819[工学-矿业工程] 0808[工学-电气工程] 020205[经济学-产业经济学] 0818[工学-地质资源与地质工程] 0708[理学-地球物理学] 0807[工学-动力工程及工程热物理] 0816[工学-测绘科学与技术] 

基　　金：Pandit Deendayal Petroleum University School of Petroleum Technology Department of Chemical Engineering, Universiti Teknologi Petronas 

主　　题：Artificial neural network Enhanced oil recovery Fuzzy logic system Artificial lift Permeability Porosity 

摘      要：In the Oil and Gas industry,the implementation of artificial intelligence techniques gives advantages of better use of existing *** provides better future outcomes,which makes it an essential technology in the operations of the *** this paper,the implementation of artificial intelligence techniques for good planning,determination of reservoir rock properties,drilling optimization and production facilities are *** precise knowledge of permeability and porosity,reservoir engineers can develop robust reservoir development plan and manage hydrocarbon recovery *** porosity prediction,wire-line log data and seismic attributes are used in artificial intelligence-based *** prediction has been discussed by considering the different types of well-log data in the modeling of artificial intelligence techniques to predict single-phase *** of specific developed problems during the determination of permeability in the actual experiment is also *** intelligence techniques are used in the design and accurate analysis of the drilling *** assists in the selection of drill bit and drilling-related *** a reservoir cannot produce naturally,we can select a suitable artificial lift and design the production system using Artificial intelligence *** EOR methods,SADA and NAVA knowledge base systems are *** intelligence can help in optimizing production,improve production efficiency and recovery of hydrocarbons.