大数据思维下的矿产资源评价

Mineral resources assessment under the thought of big data

以大数据时代的预测思维方法,结合重要矿产资源潜力评价具体工作,探索了矿产资源预测评价的基本理论基础。认为大数据的相关性预测方法和常用的综合信息矿产预测方法是一致的,矿产预测模型理论、多学科信息相关性分析、预测地质求异理论、矿产区域趋势分析方法是矿产资源评价的四项基本理论。总结了在数字化、信息化时代矿产资源预测评价的主要工作流程。建立数字化预测数据平台、根据预测矿产模型进行数据清洗、编制预测要素图件、建立预测模型、圈定预测靶区和成矿远景区、进行资源潜力估算等是预测评价的基本任务与流程。

In this paper, the basic theoretical foundation of mineral resources prediction and evaluation is explored, with the prediction thinking method in the age of Big Data and the work of the mineral resources potential assessment in details. It is considered that the prediction method of the big data is relativity consistent with the common comprehensive information mineral prediction method. The four fundamental theories include mineral prediction model theory, multidisciplinary information correlation analysis, geological theory of dissimilation and trend analysis of mineral area. The main workflow of mineral resources assessment in the information age and digital era is summarized. The basic tasks and processes are building the data platform for digital prediction, data cleaning according to mineral prediction model, preparing the forecast figure, building prediction model, delineating metallogenic target area and minerogenic prospect, and estimating the potential resources.