地质通报2026，Vol.45Issue(7)：1219-1236,18.DOI:10.12097/gbc.2025.08.028
人工智能技术在地质找矿中的应用及未来发展方向
Application and future development directions of artificial intelligence technology in geological prospecting
摘要
Abstract
[Objective]Faced with the increasing difficulty in exploring deep and concealed ore deposits,traditional methods have shown their limitations.Therefore,systematically evaluating the pathways and potential of an AI-driven paradigm shift in mineral exploration is of great practical significance.[Methods]This paper systematically sorts out the development context and key technologies of AI in the field of geological prospecting,and reveals the in-depth coupling relationship between technological evolution and the demands of geological prospecting.It elaborates on the application mechanisms and practical effects of AI in key scenarios such as geological mapping,mineralization prediction,mineral identification,and geophysical inversion.[Results]Despite its broad application prospects,artificial intelligence still faces key technical bottlenecks at present,such as difficulties in fusing multi-source heterogeneous geological data,insufficient generalization ability of prospecting models,and the construction of geological large models.[Conclusions]This paper argues that realizing data standardization,developing knowledge-guided intelligent prospecting models,and constructing large mineral geological models are the keys to breaking through current bottlenecks.The collaborative research of these three directions will substantially promote the paradigm shift of geological work from"experience-driven"to an intelligent decision-making paradigm driven by"data and knowledge integration".关键词
智能找矿/矿产勘查/地质大模型/人工智能技术/数据标准化Key words
intelligent mineral exploration/mineral exploration/geological large models/artificial intelligence applications/data standardization分类
天文与地球科学引用本文复制引用
王春女,甄世民,邢万里..人工智能技术在地质找矿中的应用及未来发展方向[J].地质通报,2026,45(7):1219-1236,18.基金项目
中国地质调查局项目《大数据智能找矿预测》(编号:DD20242591) Supported by the project of China Geological Survey(No.DD20242591) （编号:DD20242591）
