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ARTIFICIAL INTELLIGENCE AS A TOOL FOR EVALUATING THE EFFICIENCY OF INNOVATIVE TECHNOLOGIES FOR HARD-TO-RECOVER RESERVES DEVELOPMENT
The possibility of artificial intelligence use for improvement of efficiency of development of hard-to-recover reserves in Russian oil and gas complex are considered in research article. The share of hard-to-recover reserves increases annually in cumulative oil production in the territory of the Rus...
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Published in: | International review (Faculty of Business Economics and Entrepreneurship) 2021, Vol.2021 (3-4), p.30-35 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | The possibility of artificial intelligence use for improvement of efficiency of development of hard-to-recover reserves in Russian oil and gas complex are considered in research article. The share of hard-to-recover reserves increases annually in cumulative oil production in the territory of the Russian Federation, therewith ups and downs of prices for oil well-known brands increase the risks of unforeseen costs and material losses when developing new reserves, that is why the authors establish a goal to analyze the efficiency of geological exploration and development of oil hard-to-recover reserves using artificial intelligence technologies and also based on the calculation of a comparative model for assessing the use of artificial intelligence on groups of fields of the Bazhenov formation.Artificial intelligence can have a beneficial effect on decrease of human error risk when selecting potential cased holes and facilitate in choosing the best methods of development and feed production stimulation. As a result of the comparative assessment of the return on investment in the development of wells using artificial intelligence and traditional technologies, the advantages and disadvantages of AI technologies were identified in the context of increasing the economic efficiency of hard-to-recover oil production. |
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ISSN: | 2217-9739 2560-3353 |
DOI: | 10.5937/intrev2103030C |