3D geostatistical modelling for identifying sinkhole disaster potential zones around the Verkhnekamskoye potash deposit (Russia)

Abstract

This work results from a cooperative scientific program between the Perm State University (Russia) and the University of Lorraine (France). Its objectives are to integrate modern 3D geomodeling in order to improve sustainable mining extraction, especially for predicting and avoiding the formation of sinkholes disaster potential zones. Systematic exploration drill holes performed in the Verkhnekamskoye potash deposit (Perm region, Russia) have been used to build a comprehensive 3D model for better understanding the spatial repartition of the ore quality (geometallurgy). A precise modelling of the mineralized layers allows an estimation of the in-situ ore reserves after interpolating by kriging the potassium (K) and magnesium (Mg) contents at the node of a regular centred grid (over a million cells). Total resources in potassium vary according to the cut-off between 4.7Gt @ 16.1 % K2O; 0.32 % MgCl2 for a cut-off grade at 13.1% K2O and 2.06 Gt @ 18.2 % K2O; 0.32 % MgCl2 at a cut-off of 16.5% K2O. Most of reserves are located in the KPI, KPII and KPIII layers, the KPI being the richest, and KPIII the largest in terms of tonnage. A systematic study of the curvature calculated along the roof of the mineralized layers points out the location of potential main faults which play a major role in the formation of sinkhole during exploitation. A risk map is then derived from this attribute.