Application of machine learning and deep learning in geothermal resource development: Trends and perspectives
Abstract This study delves into the latest advancements in machine learning and deep learning applications in geothermal resource development, extending the analysis up to 2024. It focuses on artificial intelligence's transformative role in the geothermal industry, analyzing recent literature f...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-09-01
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| Series: | Deep Underground Science and Engineering |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/dug2.12098 |
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| _version_ | 1846168001550745600 |
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| author | Abdulrahman Al‐Fakih Abdulazeez Abdulraheem Sanlinn Kaka |
| author_facet | Abdulrahman Al‐Fakih Abdulazeez Abdulraheem Sanlinn Kaka |
| author_sort | Abdulrahman Al‐Fakih |
| collection | DOAJ |
| description | Abstract This study delves into the latest advancements in machine learning and deep learning applications in geothermal resource development, extending the analysis up to 2024. It focuses on artificial intelligence's transformative role in the geothermal industry, analyzing recent literature from Scopus and Google Scholar to identify emerging trends, challenges, and future opportunities. The results reveal a marked increase in artificial intelligence (AI) applications, particularly in reservoir engineering, with significant advancements observed post‐2019. This study highlights AI's potential in enhancing drilling and exploration, emphasizing the integration of detailed case studies and practical applications. It also underscores the importance of ongoing research and tailored AI applications, in light of the rapid technological advancements and future trends in the field. |
| format | Article |
| id | doaj-art-e2b97c5fdcf34a48933f9a11a7b565d3 |
| institution | Kabale University |
| issn | 2097-0668 2770-1328 |
| language | English |
| publishDate | 2024-09-01 |
| publisher | Wiley |
| record_format | Article |
| series | Deep Underground Science and Engineering |
| spelling | doaj-art-e2b97c5fdcf34a48933f9a11a7b565d32024-11-14T12:11:23ZengWileyDeep Underground Science and Engineering2097-06682770-13282024-09-013328630110.1002/dug2.12098Application of machine learning and deep learning in geothermal resource development: Trends and perspectivesAbdulrahman Al‐Fakih0Abdulazeez Abdulraheem1Sanlinn Kaka2College of Petroleum Engineering and Geosciences King Fahd University of Petroleum Minerals Dhahran Saudi ArabiaCollege of Petroleum Engineering and Geosciences King Fahd University of Petroleum Minerals Dhahran Saudi ArabiaCollege of Petroleum Engineering and Geosciences King Fahd University of Petroleum Minerals Dhahran Saudi ArabiaAbstract This study delves into the latest advancements in machine learning and deep learning applications in geothermal resource development, extending the analysis up to 2024. It focuses on artificial intelligence's transformative role in the geothermal industry, analyzing recent literature from Scopus and Google Scholar to identify emerging trends, challenges, and future opportunities. The results reveal a marked increase in artificial intelligence (AI) applications, particularly in reservoir engineering, with significant advancements observed post‐2019. This study highlights AI's potential in enhancing drilling and exploration, emphasizing the integration of detailed case studies and practical applications. It also underscores the importance of ongoing research and tailored AI applications, in light of the rapid technological advancements and future trends in the field.https://doi.org/10.1002/dug2.12098artificial intelligencedeep learninggeothermal energy developmentmachine learning |
| spellingShingle | Abdulrahman Al‐Fakih Abdulazeez Abdulraheem Sanlinn Kaka Application of machine learning and deep learning in geothermal resource development: Trends and perspectives Deep Underground Science and Engineering artificial intelligence deep learning geothermal energy development machine learning |
| title | Application of machine learning and deep learning in geothermal resource development: Trends and perspectives |
| title_full | Application of machine learning and deep learning in geothermal resource development: Trends and perspectives |
| title_fullStr | Application of machine learning and deep learning in geothermal resource development: Trends and perspectives |
| title_full_unstemmed | Application of machine learning and deep learning in geothermal resource development: Trends and perspectives |
| title_short | Application of machine learning and deep learning in geothermal resource development: Trends and perspectives |
| title_sort | application of machine learning and deep learning in geothermal resource development trends and perspectives |
| topic | artificial intelligence deep learning geothermal energy development machine learning |
| url | https://doi.org/10.1002/dug2.12098 |
| work_keys_str_mv | AT abdulrahmanalfakih applicationofmachinelearninganddeeplearningingeothermalresourcedevelopmenttrendsandperspectives AT abdulazeezabdulraheem applicationofmachinelearninganddeeplearningingeothermalresourcedevelopmenttrendsandperspectives AT sanlinnkaka applicationofmachinelearninganddeeplearningingeothermalresourcedevelopmenttrendsandperspectives |