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  • 标题:AI-based geo-engineering integration in unconventional oil and gas
  • 本地全文:下载
  • 作者:Shiying Di ; Shiqing Cheng ; Nai Cao
  • 期刊名称:Journal of King Saud University - Science
  • 印刷版ISSN:1018-3647
  • 出版年度:2021
  • 卷号:33
  • 期号:6
  • 页码:1-9
  • DOI:10.1016/j.jksus.2021.101542
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractIn the oil and natural gas industry, artificial intelligence (AI) technology has penetrated into all links from exploration and development to construction sites. This paper investigates the application of artificial intelligence in each link of oil reservoir. It is found in investigation that each algorithm plays a different and important role at each stage and every link of oil accumulation development cannot leave the cooperation of artificial intelligence. But, the application of AI is mostly scattered, forming a physical isolation, a lot of single information-island. This situation increases the communication cost of cross-departmental data cooperation and the repetitive screening and recognition work has seriously affected work efficiency. To address unsolved problems with the current application of AI, AI-based geo-engineering integration in unconventional oil and gas are proposed this article considers. Integrate data islands, and realize internal resource sharing, treat exploration and development as an organic whole, extend exploration to development. This article takes the well factory operation mode, meanwhile, the real-time synchronization and coordination of all links has been fully realized. This kind of integration of geology and engineering is helpful to realize coordination and cooperation at all levels, regions, and disciplines, effectively benefiting development of unconventional oil and gas reservoirs.
  • 关键词:Artificial intelligence algorithm;Unconventional reservoir;Engineering integration;Geo-engineering integration;Exploration and development
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