Uncertainty quantification of rock quality designation at the Gazestan phosphate deposit

Several geomechanical variables reflect the characteristics of rock masses and in recent years have been considered as the geometallurgical responses in the mining industry. These variables have a great effect on the energy consumption and in further stages of mineral processing, impacting the throughput of the grinding circuit, metal recovery, and reagent consumption For instance, rock quality designation (RQD) is not only a very popular parameter used to define domains with excellent and poor physical properties, but can also be used to predict relative throughput rates in a SAG milling circuit. Geostatistical modelling of this regionalized variable is significant and nonlinear Geostatistics can be employed for the spatial quantification. In this study, the multi- Gaussian kriging approach is adopted as a nonlinear geostatistical technique for probabilistic domaining of RQD at unsampled locations at a phosphate deposit in Iran. The resulting estimates are checked thoroughly by cross-validation and can be used for defining the probable areas dominated by soft, moderate, and hard rocks applicable for mine design and mineral processing plant optimization..