摘要:大数据思维是直接从数据入手的一种新的思维方式，其本质是减少甚至完全屏蔽人为因素干扰，让数据说话。以往三维成矿预测中指标体系的建立多采用经验分析法，以地质模型和先验知识指导控矿特征变量取值，其准确性易受到人为影响。本文基于大数据思维，使用数据驱动方法对三维成矿预测中的找矿指标体系进行探索性研究，在钟姑矿田选择4 个大中型典型矿床，直接采用三维空间分析方法对地层和岩体的控矿地质体进行特征分析，通过计算z 轴方向三维距离场、分析岩体顶面隆起凹陷程度形态因素，确定各控矿要素与矿体之间的相关关系，获取定量指标。本研究改变了以往主观经验指导找矿的思路，尝试采用空间数据挖掘方法进行客观数据分析提出找矿指标，提高了找矿指标体系建立的科学性，此方法得到的定量指标体系可直接参与三维找矿预测模型的计算。?
关键词: 大数据/
三维成矿预测/
空间数据挖掘/
定量指标体系/
钟姑矿田
Abstract:Big data thinking is a new thinking mode starting with the data directly. Its essence is to reduce or even completely shield human’s interference and let the data speak for itself. In the past, the establishments of quantitative indicators in 3D prospectivity mapping were mostly by empirical analysis, using geological model and prior knowledge to guide the determination of ore-controlling characteristic variables. However, the accuracy of this method is sensitive to human factors. Based on big data thinking, a data-driven method is applied to explore the prospecting indicator sets in 3D prospectivity mapping. We select four large and medium-sized typical deposits in the Zhonggu ore field and apply a 3D spatial analysis method to analyze the ore-controlling geological bodies of strata and rocks. Based on calculating the 3D distance field in z-axis and analyzing the top morphology of rocks, the relationship between ore controlling factors and ore bodies is determined, and quantitative sets are obtained. This research attempts to use the spatial data mining method to carry on the objective data analysis instead of prospecting guided by subjective experience, which enhances the scientificity of the prospecting indicator system. Quantitative indicators acquired through this method can be used in the 3D prospectivity mapping directly.?
Key words:Big data/
3D prospectivity prediction/
Spatial data mining/
Quantitative indicators/
Zhonggu ore field
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