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.
Zhang Mingming Shen le Liao Baosheng Li Xiaohui Yuan Feng Zhou Yuzhang. Research on the quantitative indicators for 3D prospectivity prediction based on spatial data mining：A case study of Zhonggu ore field in Ningwu Basin[J]. Chinese Journal of Geology, 2018, 53(4): 1300-1313.