| “深部综合信息矿产资源预测评价”专辑特邀主编寄语 |
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| 关键词:three dimensional prediction three dimensional model of metallogenic structure metallogenic regularity machine learning |
| 基金项目:国家重点研发计划“深地资源勘查开采”重点专项课题(编号: 2017YFC0601501);“深部成矿地质异常定量预测方法与模型”(编号: 2017YFC0601502);中国地质科学院矿产资源研究所核心业务(编号: DD20190193(N1914-03)) |
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| Guest Editor’s Preface to the “Prediction and Assessment of Deep Mineral Resources Based on Integrated Geoinformation” |
| Prediction and assessment of deep mineral resources based on integrated geoinformation is the most interdisciplinary field in earth system science. With the decrease of surface deposits, shallow deposits and deposits which are easily identified, geological prospecting has gradually developed toward the second deep space. The three-dimensional prediction has become the key field of current metallogenic prediction research. Based on a long-term continuous research, geologists have obtained a series of major achievements and important understandings in the three-dimensional prediction. The special issue (No. 2, 2020) of Acta Geoscientica Sinica contains 15 papers concerning the prediction and assessment of deep mineral resources based on integrated geoinformation. This special issue covers the following three subjects: (1) three dimensional prediction, (2) geological survey and research, and (3) geological and geochemical data processing methods. These papers mainly discuss the three-dimensional reconstruction method of deep structure, the application of isotopic dating and tracing in metallogenic regularity study, and the geochemical anomaly analysis method. This introduction aims to briefly describe each study in the three subjects, in order to provide some reference for the further studying and understanding of the prediction and assessment of deep mineral resources. |
| XIAO Ke-yan.2020.Guest Editor’s Preface to the “Prediction and Assessment of Deep Mineral Resources Based on Integrated Geoinformation”[J].Acta Geoscientica Sinica,41(2):130-134. |
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