深度学习及其在地质领域中的应用  

Deep learning and its application in geology

作　　者：刘晓梅 李新虎[1,2,3] 马天录 赵元元 LIU Xiaomei;LI Xinhu;MA Tianlu;ZHAO Yuanyuan(College of Geology and Environment,Xi'an University of Science and Technology,Xi'an 710054,Shaanxi,China;Shaanxi Provincial Key Laboratory of Geological Support for Coal Green Exploitation,Xi'an 710054,Shaanxi,China;Key Laboratory of Coal Resources Exploration and Comprehensive Utilization,Ministry of Land and Resources,Xi'an 710021,Shaanxi,China;Yangchangwan Coal Mine,National energy group Ningxia Coal industry Co.Ltd.,Yinchuan 750000,Ningxia,China;College of Information Engineering,Xi'an University of Science and Technology,Xi'an 710054,Shaanxi,China)

机构地区：[1]西安科技大学地质与环境学院,陕西西安710054 [2]陕西省煤炭绿色开发地质保障重点实验室,陕西西安710054 [3]国土资源部煤炭资源勘查与综合利用重点实验室,陕西西安710021 [4]国家能源集团宁夏煤业有限责任公司羊场湾煤矿,宁夏银川750000 [5]西安科技大学通信与信息工程学院,陕西西安710054

出　　处：《矿产勘查》2024年第2期281-291,共11页Mineral Exploration

基　　金：国家自然科学基金(41502137)资助。

摘　　要：深度学习技术的快速发展将成为地质领域再出发的助推剂,深度学习是人工智能范畴内的一个重要分支,是一种以人工神经网络为基本框架,从大量历史数据中学习规律并预测新数据的算法。为了充分理解深度学习在地质领域的应用价值,明确其在地质领域应用中存在的挑战和机遇,本文在系统阐述深度学习的发展过程、方法分类以及常见的4种深度学习模型的基础上,对比了它们在地质领域应用的特点和优势。主要从基础地质、地质勘探、地质灾害以及水文地质4个方面介绍了深度学习在地质领域应用的研究和进展,最后根据现有的情况给出了未来发展的建议,为深度学习在地质领域中应用可能遇到的机遇和挑战提供参考。The rapid development of deep learning technology will become a booster for the re-start of the geological field.Deep learning is an important branch in the field of artificial intelligence.It is an algorithm that takes artificial neural network as the basic framework to learn rules from a large number of historical data and predict new data.In order to fully understand the application value of deep learning in the field of geology,and clarify the challenges and opportunities of its application in the field of geology.On the basis of systematically describing the development process,method classification and four common deep learning models,this paper compares the characteristics and advantages of their application in the geological field,introduces the research progress of the application of deep learning in basic geology,geological exploration,geological hazards,hydrogeol⁃ogy,and gives suggestions for future development according to the existing situation,It provides reference for the opportunities and challenges that may be encountered in the application of deep learning in the geological field.

关 键 词：深度学习 神经网络 监督学习 无监督学习 地质领域 

分 类 号：TP39111[自动化与计算机技术—计算机应用技术]