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Applications of artificial intelligence in geothermal resource exploration: A review

Deep Underground Science and Engineering 2024年第3期3卷 269-285页

作者： mahmoud algaiar Mamdud Hossain Andrei Petrovski Aref Lashin Nadimul Faisal School of Engineering Robert Gordon UniversityAberdeenUK National Subsea Centre AberdeenUK Petroleum and Natural Gas Engineering Department College of EngineeringKing Saud UniversityRiyadhSaudi Arabia

Artificial intelligence (AI) has become increasingly important in geothermal exploration,significantly improving the efficiency of resource *** review examines current AI applications,focusing on the algorithms used,the challenges addressed,and the opportunities *** addition,the review highlights the growth of machine learning applications in geothermal exploration over the past decade,demonstrating how AI has improved the analysis of subsurface data to identify potential *** techniques such as neural networks,support vector machines,and decision trees are used to estimate subsurface temperatures,predict rock and fluid properties,and identify optimal drilling *** particular,neural networks are the most widely used technique,further contributing to improved exploration ***,the widespread adoption of AI in geothermal exploration is hindered by challenges,such as data accessibility,data quality,and the need for tailored data science training for industry ***,the review emphasizes the importance of data engineering methodologies,data scaling,and standardization to enable the development of accurate and generalizable AI models for geothermal *** is concluded that the integration of AI into geothermal exploration holds great promise for accelerating the development of geothermal energy *** effectively addressing key challenges and leveraging AI technologies,the geothermal industry can unlock cost‐effective and sustainable power generation opportunities.

关键词： artificial intelligence geothermal energy geothermal exploration geothermometry hidden/blind geothermal resources machine learning

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