Using borehole geophysical data as soft information in indicator kriging for coal quality estimation

Abstract Mineral resources estimation comprises basically two stages: (i) data collection, analysis and validation, and (ii) the estimate of the grades and tonnes of the deposit. The most often applied method for obtaining geological data during mineral exploration is rotary drilling with total core recovery. High drilling costs make borehole geophysical logging attractive to obtain the maximum possible information from each borehole helping to understand ore intersections, grades variability, and extension of the deposit and its continuity. In this paper, borehole geophysical logging was used to enhance the sampling survey and to derive grades indirectly (without lab analysis) with a certain amount of uncertainty. Soft indicator kriging (IK) was selected to estimate coal quality by combining hard data from drill holes and soft data from geophysical logging correlation. The method showed to be adequate to incorporate the uncertainty associated with the geophysical derived grade values. The results were compared to the conventional procedures using grades determined via core analysis and ordinary kriging. Borehole geophysical logging proved to be essential to define the features of ore deposit and soft IK provided results with acceptable precision and accuracy if compared to the model provided by ordinary kriging and hard data.