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.
| Original language | English |
|---|---|
| Pages (from-to) | 286-301 |
| Number of pages | 16 |
| Journal | Deep Underground Science and Engineering |
| Volume | 3 |
| Issue number | 3 |
| DOIs | |
| State | Published - Sep 2024 |
Bibliographical note
Publisher Copyright:© 2024 The Authors. Deep Underground Science and Engineering published by John Wiley & Sons Australia, Ltd on behalf of China University of Mining and Technology.
Keywords
- artificial intelligence
- deep learning
- geothermal energy development
- machine learning
ASJC Scopus subject areas
- Engineering (miscellaneous)
