RESOURCES ESTIMATION OF GOLD VEIN DEPOSIT USING MULTIVARIATE GEOSTATISTICAL METHOD

• Main Author: Sirait, Joseph
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/57317
• Institution: Institut Teknologi Bandung

Exploration activity is indispensable to minimize the risks inherent in the mining industry where exploration must provide complete information about the deposit such as the resource estimation model. Resource estimation using conventional or linear geostatistical methods sometimes produces less accurate results. Therefore the nonlinear geostatistical method such as multivariate geostatistics is expected to provide more accurate estimation. The case study for this research is Pongkor gold veins located in the district of Bogor, West Java, Indonesia about 80 km southwest of Jakarta or at the northeastern side of the Dome Bayah. Gold and silver mineralization was contained in Pongkor gold vein deposit. This study aims to determine the results of the estimated blocks and their variance estimation on Au-Ag grades using Ordinary Cokriging (COK) as one of multivariate geostatistical methods. However the linear geostatistical method such as Ordinary Kriging (OK) as frequently used methods was performed for comparison. Both methods were validated using composited data by considering the slope of regression and coefficient of correlation between estimated grades and composited actual grades. The Au-Ag assays data was divided into two parts, i.e. data without top cut and data using top cut. Variogram of Au-Ag grades and their cross-variogram were used as estimation parameters for COK and OK. The correlation coefficient of estimated grades and composited actual data showed the strong correlation with coefficient more than 0.6. COK produced smaller estimation variances on Au-Ag estimates than OK method. Grade-tonnage curve on block estimation was established to see the difference in the estimation results of both methods.The data with and without top cut showed no significant different in the validation results.