Application and development trend of artificial intelligence in petroleum exploration and development
Применение и тенденции развития искусственного интеллекта в разведке и разработке нефтяных месторождений
2021-02-01
SCID: 54.1/bh3crb5p
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artificial intelligencedeep learningintelligent drillingmachine learningpetroleum exploration
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Abstract (AI)
Aiming at the actual demands of petroleum exploration and development, this paper describes the research progress and application of artificial intelligence (AI) in petroleum exploration and development, and discusses the applications and development directions of AI in the future. Machine learning has been preliminarily applied in lithology identification, logging curve reconstruction, reservoir parameter estimation, and other logging processing and interpretation, exhibiting great potential. Computer vision is effective in picking of seismic first breaks, fault identification, and other seismic processing and interpretation. Deep learning and optimization technology have been applied to reservoir engineering, and realized the real-time optimization of waterflooding development and prediction of oil and gas production. The application of data mining in drilling, completion, and surface facility engineering etc. has resulted in intelligent equipment and integrated software. The potential development directions of artificial intelligence in petroleum exploration and development are intelligent production equipment, automatic processing and interpretation, and professional software platform. The highlights of development will be digital basins, fast intelligent imaging logging tools, intelligent seismic nodal acquisition systems, intelligent rotary-steering drilling, intelligent fracturing technology and equipment, real-time monitoring and control of zonal injection and production.
Key Findings
1
Computer vision is effective for seismic processing and interpretation tasks such as first-break picking and fault identification.
2
Data mining applied to drilling, completion, and surface-facility engineering has supported the development of intelligent equipment and integrated software.
3
Deep learning and optimization methods enable real-time waterflooding optimization and oil-and-gas production prediction in reservoir engineering.
4
Future AI development is expected to emphasize intelligent production equipment, automated processing and interpretation, professional software platforms, and systems including digital basins and intelligent drilling, fracturing, and injection-production control.
5
Machine learning has shown strong potential in logging applications, including lithology identification, logging-curve reconstruction, and reservoir-parameter estimation.
Research Object
Artificial intelligence applications in petroleum exploration and development
Research Subject
The research progress, applications, and future development directions of AI for petroleum exploration, development, processing, interpretation, engineering, and production optimization
Publication Details
Publication Date
2021-02-01
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