Indirect modeling of spatial distribution of gold grade using the integration of IP-RS data and associated sulfide paragenes in the range of Yangani and Qinrjeh (zarshuran)

The study area is the Yeganlly and Qinranjeh area, southwest of Zarshuran gold mine, 35 km away from Takab city, West Azarbaijan province. The study area is located on the southwest edge of the mine. Only 17 borehole data were available for this study and were evaluated. Geophysical data includes 17 parallel profiles with a length of about 735 meters with a 30 meter distance electrode and a polar-bipolar mapping array according to the topography of the area. The objective of introducing and presenting a method for simulation and single-multivariate estimation using the most widely used methods, such as usual cracking, ordinary cokriging, sequential simulation, sequential coexistence simulation, in order to reproduce more precisely the initial region variables and Secondary will be. Geophysical data was constructed of a so-called sulfide factor. After normalizing, for each variable, the variography chart was drawn and estimated using the Kriging method according to the variogram in the borehole coordinates. Then, by normalizing the data in the specimen, analysis of the main components on the variables was performed using SPSS software. The output of this part was two factors that the fact that the amount of gold mineralization was high was introduced as a mineralization factor. Now, with two existing factors, namely, the sulfide factor (geophysical factor) and the gold mineralization factor in the studied area, the combined interactions between the built-in block models were combined with the estimation and simulation; ultimately, validation was also performed by evaluating and estimating two boreholes Isolated randomly using other specimens at the end. It was found that according to the evaluated results, when estimating the gold grade when using sulfide factors and mineralization in coking, the gold monorangle estimation by conventional Kriging estimation is closer to the real values of gold.