智能矿山大数据的地学信息挖掘与知识发现:以河南上房沟钼(铁)5G^(+)矿山为例  

Intelligent geoscience information mining and knowledge discovery using big data analytics:A case study of the Shangfanggou Mo(Fe)mine in Henan Province

作　　者：王洛锋 王功文[2,3,4] 许文辉 徐森民 何亚清 王春毅 杨涛 周晓将 黄蕾蕾 左玲 牟妮妮 曹毅 刘志飞[2] 常瑜琳 WANG Luofeng;WANG Gongwen;XU Wenhui;XU Senmin;HE Yaqing;WANG Chunyi;YANG Tao;ZHOU Xiaojiang;HUANG Leilei;ZUO Ling;MOU Nini;CAO Yi;LIU Zhifei;CHANG Yulin(China Molybdenum Co.,Ltd.,Luoyang 471500,China;School of Earth Sciences and Resources,China University of Geosciences(Beijing),Beijing 100083,China;Beijing Key Laboratory of Land and Resources Information Research and Development,Beijing 100083,China;MNR Key Laboratory for Exploration Theory&Technology of Critical Mineral Resources,China University of Geosciences(Beijing),Beijing 100083,China)

机构地区：[1]洛阳栾川钼业集团股份有限公司,河南洛阳471500 [2]中国地质大学(北京)地球科学与资源学院,北京100083 [3]北京市国土资源信息开发研究重点实验室,北京100083 [4]自然资源部战略性金属矿产找矿理论与技术重点实验室,北京100083

出　　处：《地学前缘》2023年第4期317-334,共18页Earth Science Frontiers

基　　金：洛阳栾川钼矿业集团项目“上房沟钼矿床矿物高光谱勘查与三维建模研究”(2021—2022);中国地质大学(北京)地质调查成果转化基金资助项目(2020—2021)(42932019022)。

摘　　要：21世纪工业4.0促进了智能矿山诞生,智能矿山的地质、勘探、采矿、选矿、环境、测绘等多学科数据集构成了矿山大数据,从而促进了地球科学的数字化、信息化和智能化迅速发展。本文以河南上房沟钼(铁)矿床5G^(+)智能矿山为例,开展矿山大数据的地学信息挖掘,以凸显新工科多学科融合研究,取得了创新性成果与一系列新的地学知识发现。具体内容概括如下:(1)根据“斑岩-夕卡岩”矿床理论和找矿矿物学方法,利用钻孔数据集和露采场大比例尺填图及镜下鉴定分析,查明并构建了矿区主矿种与潜在矿种的时空三维模型,新发现了NE向构造赋矿地段、贯入式赋矿地段;(2)利用无人机遥感与地面高光谱短波红外和长波红外技术,识别并建立了矿区20多种主要蚀变矿物并构建了三维多参数矿物模型;(3)运用地球化学XRF测量和微区原位测量技术,建立了高光谱匹配的样品数据集,研发了矿区岩矿石有用和有害元素双矩阵制图软件,实现了传统地质统计学(高斯模拟、克里格插值)与机器学习(深度学习)关联的数学建模,复原并查明了2021年3—4月选矿回收率偏低的配矿矿石矿物组合及其缘由;(4)运用矿区选矿工艺矿物学的生产与实验采选矿的多期次多类型数据集(季-月-日的岩粉、泥粉、精矿、尾矿等,>1 800),研发岩粉与矿粉测试技术与分析方法,查明了上房沟钼矿的难选矿石类型及其有害矿物种类。研究结果表明,矿山多元多类型的数据集具有大数据“5V”(volume, variety, velocity, veracity, value)特征,准确管控矿山大数据的动态关联测量、分析与快速、高效评价有利于矿山智能决策和经济效益提高(回收率)。其中,高精度的多参数三维建模不仅能够深层次挖掘岩矿石的地质、构造、蚀变、矿化等信息模型,核实储量/资源量,还能满足第四代工业5G^(+)矿山的实时矿业(real-time-mining)�Industry 4.0 of the 21 st century has given birth to smart mines.The multidisciplinary datasets of smart mines-such as geology,exploration,mining,geometallurgy,environment and survey/map datasets-constitute big data of mines,and they play an important role for the rapid advancements of geoscience in areas of geoscience digitization and application of information/Al technology in geoscience.Taking the Shangfanggou Mo(Fe)mine,a 5G^(+)smart mine,in Henan Province as an example,using big data of mines,this paper carried out geoscience information mining to highlight emerging engineering research with integrated multidisciplinary approach.Innovative results and geological knowledge discoveries from this study are summarized as follows:(1)According to theories on porphyry-associated skarns and mineralogical approach to minera resources prospecting,using borehole datasets and large-scale open-pit mapping and microscopic identification analysis,a 3D temporo-spatial model of the identified key minerals and predicted minerals in the study area was established,and a NE trending ore-bearing fault section and a penetration-type ore-bearing section were discovered.(2)Using UAV remote sensing and ground hyperspectral short-wave/long-wave infrared techniques,more than 20 types of key altered minerals in the study area were delineated,and a 3D multi-parameter mineral model was constructed.(3)Using geochemical techniques such as XRF and in-situ microscopy,a rock dataset with matching hyperspectral interpretation was established,and a dual-matrix mapping software for useful/harmful elements of rocks/ores in the study area was developed.In addition,mathematical modeling combining traditional geostatistics(gauss simulation,kriging interpolation)with machine learning(deep learning)was realized,and the composition of ore blends used between March-April 2021 was identified and the cause of the resulting low recovery rate was clarified.(4)Based on process mineralogy practice in the study area,multi-stage,multi-type mineral processing dat

关 键 词：矿山大数据 高光谱 XRF 地球化学原位分析 地学信息挖掘 知识发现 上房沟Mo多金属矿床 

分 类 号：P628[天文地球—地质矿产勘探] P618.65[天文地球—地质学]