吴冲龙,周琦,徐凯,张夏林,孔春芳,李岩,杨炳南,张遂,袁良军.用于大数据预测的大塘坡式锰矿找矿过程复盘研究[J].贵州地质,2022,39(3):189-204 |
用于大数据预测的大塘坡式锰矿找矿过程复盘研究 |
A Review Study of the Prospecting Process of Datangpo Manganese Ore used for Big Data Prediction |
投稿时间:2022-07-19 |
DOI: |
中文关键词: 地质大数据 大数据成矿预测 数字勘查 复盘 数据融合 数据挖掘 关联关系 |
英文关键词:Geological big data Big data mineralization prediction Digital survey Review Data fusion Data mining Associative relationships2022年39卷第3期(总第152期)贵州地质GUIZHOUGEOLOGYVol39No3(Tol152)2022 |
基金项目:中央引导地方科技发展资金项目“锰矿资源深部预测勘查技术研发基地”([2021]4027);贵州省找矿突破战略行动重大协同创新项目“贵州磷、锰、铝优势资源成矿规律与快速高效智慧化勘查技术研究及示范”([2022]ZD003);贵州省“锰矿勘查与开发大数据管理与智能处理系统研发应用”(黔科合支撑[2017]2951);贵州省锰矿资源预测评价科技创新人才团队(黔科合平台[2018]5618);贵州省高层次创新人才项目(黔科合平台人才[2018]5631-2,[2020]6019)。 |
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中文摘要: |
本文提供一个试验性工作的初步总结。通过数据驱动方式对黔东北地区“大塘坡式”锰矿找矿过程进行“复盘”,一方面找到了构建相关知识图谱的办法,另一方面找到了优化实际找矿过程的途径。在此基础上,把基于地质学和矿床学基础知识的“有模型”预测,与基于第四范式的“无模型”预测结合起来,进而组织大数据集和大数据链,便可建立数据-模型联合驱动的锰矿综合预测模式。基于数据-模型联合驱动的成矿预测,涉及地质、物探、化探、遥感数据的广度聚联和深度挖掘,是一项复杂的系统工程,应当着重加强整体逻辑过程研究及其数据链组织;同时需要有地矿勘查工作数字化转型的配合,应当研发并应用基于大数据的数字勘查和成矿预测技术体系,以及相应的大数据采集、管理和融合的基础设施。 |
英文摘要: |
This article provides a preliminary summary of the pilot workThrough the data-driven “review” of the “Datangpo-type” manganese ore prospecting process in the Northeast Guizhou,on the one hand,a way to build a relevant knowledge graph was found,and on the other hand,a way was found to optimize the actual prospecting processOn this basis,by combining the “have model” prediction based on the basic knowledge of geology and mineral deposits with the “modelless” prediction based on the fourth normal form,and then organizing the big data set and big data chain,a data-model combine driving manganese ore comprehensive prediction model can be establishedBased on data-model combine driving mineralization prediction,it involves extensive aggregation and indepth mining of geological,geophysical,geochemical and remote sensing data,which is a complex system engineering,and should focus on strengthening the overall logical process research and its data link organization;At the same time,it is necessary to cooperate with the digital transformation of geological and mineral exploration,and should develop and apply digital exploration and mineralization prediction technology systems based on big data,as well as corresponding big data collection,management and integrated infrastructure |
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