Applications of artificial intelligence in geothermal resource exploration: A review  

作　　者：Mahmoud AlGaiar Mamdud Hossain Andrei Petrovski Aref Lashin Nadimul Faisal 

机构地区：[1]School of Engineering,Robert Gordon University,Aberdeen,UK [2]National Subsea Centre,Aberdeen,UK [3]Petroleum and Natural Gas Engineering Department,College of Engineering,King Saud University,Riyadh,Saudi Arabia

出　　处：《Deep Underground Science and Engineering》2024年第3期269-285,共17页深地科学（英文）

摘　　要：Artificial intelligence (AI) has become increasingly important in geothermal exploration,significantly improving the efficiency of resource identification.This review examines current AI applications,focusing on the algorithms used,the challenges addressed,and the opportunities created.In 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 resources.AI 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 locations.In particular,neural networks are the most widely used technique,further contributing to improved exploration efficiency.However,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 professionals.Furthermore,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 exploration.It is concluded that the integration of AI into geothermal exploration holds great promise for accelerating the development of geothermal energy resources.By 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 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] P314[自动化与计算机技术—控制科学与工程]