This work presents a methodology to estimate iron ore reserves, which uses mineralogical data represented by the mineral specular hematite. The geostatistical methods of conditional simulation and kriging are used to characterize the specular hematite in block models. Cut-off grades and recoverable reserves are determined by using the recovery functions average grade and ore tonnage. The results showed significant differences between the kriged and the conditional simulation models.
conditional simulation; kriging; recoverable reserves; recovery functions
