Recognition of Significant Surface Soil Geochemical Anomalies Via Weighted 3D Shortest-Distance Field of Subsurface Orebodies: A Case Study in the Hongtoushan Copper Mine, NE China

Quantitative prediction of concealed mineralization is always confronted with difficulties in comprehensive analysis between 2D and 3D data and between qualitative and quantitative data. A weighted shortest-distance field method is proposed here to track, in 3D heterogeneous space, the shortest migration paths of ore-forming elements from an orebody to the ground surface, assuming that ore-forming elements migrate at less costs into fault rupture zones than in other surrounding rocks. This method was used to generate the weighted shortest-distance field of the 3D orebody model in the Hongtoushan copper mine, NE China. In addition, the field value and the geochemical soil survey data on the Earth's surface were subjected to statistical analysis. Results showed that some geochemical anomalies are characterized by the shortest-distance field of the known orebodies, while other formerly unrecognized anomalies may possibly be related to undiscovered orebodies. This method can also be applied to comprehensive statistical analysis between a 3D geological model and 2D data on the Earth's surface, e.g., geophysical exploration or remote sensing data.