Ore Deposit Boundary Modification in Afghanistan Aynak Central Copper Deposit using Sequential Indicator Simulation and Indicator Kriging

The Aynak copper deposit is the most important strata-bound copper reserve in Afghanistan. The main purpose of this work is the ore deposit boundary modification and reserve estimation of the Aynak central copper deposit using the geostatistical methods. The ordinary kiging (OK), indicator kriging (IK) and sequential indicator simulation (SIS) methods were used to modify the optimum ore deposit boundary and ore reserve estimation. Then the results, accuracy and efficiency of these three methods are compared. Before the ore reserve estimation, the pre-processing,  statistical and geostatistical analysis of the sampled data are performed. For a precise estimation process, it is necessary to modify the optimum ore body boundary as an estimation space. Therefore, the IK and SIS methods are applied to revise the conventional ore deposit boundary and estimation space. At the first stage, the ore body wireframe and solid model are obtained using the conventional cross-section method. The block model is created covering the mineralization space of the ore body, and firstly constrained by the conventional model (solid model). Consequently, the ore body model is adapted and bounded using the IK and SIS geostatistical methods. Finally, the log-kriging method that is basically unbiased and guarantees the minimum estimation error is used to estimate the Cu concentration in each block, and after back-transformation, the grade-tonnage curves are plotted. The total tonnage of the deposit is calculated based on different cut-off grades. Assuming the cut-off grade of ۰.۲% for Cu, the tonnage of ore reserve based on the conventional OK method, IK method, and SIS constrained ore body model are estimated as ۴۵۳.۴, ۴۵۹.۱, and ۴۶۷.۷ million tons with an average grade of ۱.۰۷۷%, ۱.۰۸%, and ۱.۰۵%, respectively. The proximity of the obtained reserve estimation results using different implemented methodologies is due to the low-grade variability and genetical regularity in the Aynak staratabound copper deposit and guarantees the accuracy of the results obtained in the ore reserve evaluation.

Keywords:

Geostatistics , Orebody Boundary Modeling , Indicator kriging , Sequential Indicator-Simulation , Aynak Copper Deposit