Artificial intelligence in the geothermal energy systems
bookPart
Harvesting of geothermal energy involves complex processes, including resource characterization, drilling, production, and operation. Numerous parameters and factors must be optimized to improve efficiency and minimize costs. However, despite generating vast amounts of data in every stage, they are not fully utilized to optimize processes or develop new designs. Therefore, data analytics and machine learning play a crucial role in the exploration, development, and operation of geothermal production systems. Geothermal companies and operators can identify new resources, optimize production, and predict equipment failure by analyzing large amounts of data. Machine learning models can support organizations in making informed decisions about resource development, production, and maintenance. The growth in natural language processing and large language models can provide immense opportunities in the geothermal industry, such as extracting information or automating the processing of documents, texts, logs, and publications. By leveraging artificial intelligence technologies, organizations can improve performance and reliability, reduce costs, and increase efficiency and sustainability in their geothermal production systems. © 2025 Elsevier Inc. All rights reserved
TNO Identifier
1014576
ISBN
978-044321662-6
978-044321663-3
978-044321663-3
Publisher
Elsevier
Source title
Geothermal Energy Engineering: Technology Transfer with the Oil and Gas Industry
Editor(s)
Livescu, S.
Dindoruk, B.
Dindoruk, B.
Place of publication
S.l.
Pages
349-377
Files
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