Applications of artificial intelligence in geothermal resource exploration: A review
Mahmoud AlGaiar, Mamdud Hossain, Andrei Petrovski, Aref Lashin, Nadimul Faisal
随着科技的飞速发展，机器学习和人工智能（AI）已经成为推动多个领域创新的关键力量。地热能作为一种清洁、可持续的能源形式，对于应对全球能源危机和减轻环境污染至关重要。本文重点探讨了机器学习在地热资源勘探领域的快速发展，以及人工智能如何通过优化地下数据分析来识别潜在的地热资源。尽管AI技术在这一领域的应用展现出巨大潜力，但仍面临一些挑战，如数据质量和可获取性的限制。针对这些问题，文章提出了一系列策略，旨在提升地热资源勘探的效率与生产力，从而加速清洁能源的开发与利用。
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Mahmoud AlGaiar, Mamdud Hossain, Andrei Petrovski, Aref Lashin, Nadimul Faisal. Applications of artificial intelligence in geothermal resource exploration: a review. Deep Underground Science and Engineering. 2024; 3(3): 269-285. doi:10.1002/dug2.12122
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01
本文简介：
这篇文章探讨了人工智能（AI）在地热资源勘探领域的最新应用进展。文中不仅分析了目前所采用的AI算法及其面临的挑战，还指出了AI技术在地热能勘探中潜在的应用机会。虽然过去也有针对地热领域AI应用的综述文章，但本篇文章有其独特之处，即专注于地热能源勘探方面的AI应用。这类信息在此之前并未在其他出版物中有过详尽的总结。我们相信，这篇文章由于深入探讨了计算机科学在地热能研究中的最新应用，将提供重要的见解。
Brief Introduction：
This review discusses the recent advances made in using artificial intelligence (AI) in geothermal resource exploration. It also analyzes the current use of AI algorithms, the associated AI challenges being addressed, and determines opportunities for applying AI in geothermal energy exploration. Although previous reviews on the use of AI in geothermal applications have been published, this current review differs as it focuses specifically on the application of AI in exploring geothermal energy resources. Such information has not previously been reviewed in detail in any other publication. Furthermore, we believe that this paper will be of interest to the readership of your journal because it critically describes the state-of-the-art application of computer science in geothermal energy research as a stand-alone contribution.
02
本文亮点：
详细展示了AI 方法的使用进展。
地球物理数据分析是AI最显著的应用。
神经网络是在地热勘探中各团队使用最多的AI技术。
提供了使用AI的挑战和对未来研究的建议。
大规模AI应用在地热勘探中相对新颖。
Highlights：
Progress in the use of AI methodologies is presented in detail.
Geophysical data analysis is the most notable AI application.
Neural networks are the most-used AI technique across geothermal exploration groups.
Challenges and recommendations for future research using AI are provided.
Large-scale AI application is reasonably novel in geothermal exploration.
03
通讯作者简介：
Nadimul Faisal
Nadimul Faisal（博士，注册工程师，机械工程师学会会员，材料、矿物与采矿学会会员，高等教育学会会士）是罗伯特戈登大学的表面工程与微力学教授。他的研究兴趣包括材料和结构的微力学行为分析、基于传感器的仪器力学测试，以及基于声发射（AE）传感器的状态监测。他发表了超过80篇同行评审期刊文章，拥有1项美国专利，撰写了4个书章节，并有超过50篇会议论文。他是爱丁堡皇家学会成员、EPSRC同行评审学院成员，以及英国超材料网络的成员。
Nadimul Faisal (PhD, CEng, MIMechE, MIMMM, FHEA) is a Professor of Surface Engineering & Micromechanics at Robert Gordon University. His interest includes micromechanical behaviour analysis of materials and structures, sensor based instrumented mechanical testing, and acoustic emission (AE) sensor‐based condition monitoring. He has over 80 peer‐reviewed journals, 1 US Patent, and 4 book chapters, and over 50 conference publications. He is member of Royal Society of Edinburgh's Young Academy of Scotland, EPSRC peer review College member, and member of UK's Metamaterials Network.
Mahmoud M. AlGaiar
Mahmoud M. AlGaiar 是贝克休斯公司的一名高级工程师。他在石油和天然气行业拥有超过19年的工作经验。他专长于石油和天然气井的设计与实施，工作足迹遍布北非和西非、南美及亚洲。他的技能涵盖井工程、常规和定向钻探、取心、井下工具、交钥匙项目管理和业务开发。Mahmoud 拥有机械工程学士学位和研究生文凭、金融与预算工商管理硕士学位，以及钻井与井工程理学硕士学位。目前，他正在英国阿伯丁的罗伯特戈登大学攻读博士学位，专业方向为地热资源勘探与评估。
Mahmoud M. AlGaiar is a senior well engineer at Baker Hughes in the Kingdom of Saudi Arabia. He has over 19 years of experience working in the Oil & Gas industry. He specialises in the design and execution of Oil & Gas wells and has worked in North and West Africa, South America and Asia. His skills include well engineering, conventional and directional drilling, coring, downhole tools, turnkey project management and business development. Mahmoud holds a BSc and PGDip in Mechanical Engineering, an MBA in Finance and Budgeting, and an MSc in Drilling and Well Engineering. He is currently a PhD student at Robert Gordon University, Aberdeen, UK, specialising in geothermal resource exploration and evaluation.
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刊登范围：
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Exploration and extraction of geo-resources
能源物质地下储存和提取
Energy extraction and storage
地下空间基础设施
Underground infrastructures
地质环境和废弃物地质处置
Geo-environments and waste geological disposal
深地空间科学实验
Research and testing space in deep underground
地下空间或地下工程规划，设计和施工技术
Plan， design and construction technology for underground space and engineering
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