机器学习在地球物理勘探中铀矿资源勘查的应用研究进展  

Review on the of Machine Learning Method and Application in the Geophysical Exploration of Uranium Deposit

作　　者：韩世礼 肖健 柳位 HAN Shili;XIAO Jian;LIU Wei(School of Resource Environment and Safety Engineering,University of South China,Hengyang,Hunan 421001,China;Hunan Key Laboratory of Rare Metal Minerals Exploitation and Geological Disposal of Wastes,Hengyang,Hunan 421001,China)

机构地区：[1]南华大学资源环境与安全工程学院,湖南衡阳421001 [2]湖南省稀有金属矿产开发与废物地质处置技术重点实验室,湖南衡阳421001

出　　处：《铀矿地质》2024年第3期555-564,共10页Uranium Geology

基　　金：湖南省自然科学基金(编号:2023JJ30506)资助。

摘　　要：机器学习有自动性、高准确性、可扩展性等优势,适用于大数据处理和自适应任务。在地球物理勘探中运用,可大幅提高勘探效率和准确性,促进技术进步,实现地球物理向智能化解译的发展。文章首先介绍了机器学习在地球物理领域的常用先进方法,如深度学习、深度神经网络、BP神经网络、支持向量机和随机森林的基本原理和分类特点。其次介绍了放射性勘探、地球物理测井、成矿预测和联合反演的基本原理,同时对前人在机器学习应用到这4方面地球物理领域的实际应用进行综合分析,结果表明,机器学习在这4个领域中的应用均取得了显著的效果。通过机器学习技术的应用,地球物理勘探能够取得更加全面、精准和高效的成果,同时也能推动这项技术的不断进步。Machine learning has the advantages of automation,high accuracy and scalability,which is suitable for big data processing and adaptive tasks.The application of machine learning in geophysical exploration can greatly improve the efficiency and accuracy,promote technological progress,and realize the development of geophysics to intelligent interpretation.This paper first introduced the basic principles and classification characteristics of machine learning in the field of geophysics,such as deep learning,deep neural network,BP neural network,support vector machine and random forest.Secondly,the basic principles of radiometric prospecting,geophysical well logging,metallogenic prognosis and joint inversion are introduced.At the same time,the practical application of machine learning in these four fields is comprehensively analyzed.The results showed that the application of machine learning in these four fields has achieved remarkable practical results.Through the application of machine learning technology,geophysical exploration can achieve more comprehensive,accurate and efficient results,and also promote the continuous progress of geophysical exploration technology.

关 键 词：机器学习 放射性勘探 地球物理测井 成矿预测 联合反演 

分 类 号：P631[天文地球—地质矿产勘探] TP39[天文地球—地质学]