Application of RQD-Number and RQD-Volume multifractal modelling to delineate rock mass characterisation in Kahang Cu-Mo porphyry deposit, central Iran.

Abstract

Identification of rock mass properties in terms of Rock Quality Designation (RQD) plays a significant role in mine planning and design. This study aims to separate the rock mass characterisation based on RQD data analysed from 48 boreholes in Kahang Cu-Mo porphyry deposit situated in the central Iran utilising RQD-Volume (RQD-V) and RQD-Number (RQD-N) fractal models. The log-log plots for RQD-V and RQD-N models show four rock mass populations defined by RQD thresholds of 3.55, 25.12 and 89.12% and 10.47, 41.68 and 83.17% respectively which represent very poor, poor, good and excellent rocks based on Deere and Miller rock classification. The RQD-V and RQD-N models indicate that the excellent rocks are situated in the NW and central parts of this deposit however, the good rocks are located in the most parts of the deposit. The results of validation of the fractal models with the RQD block model show that the RQD-N fractal model of excellent rock quality is better than the RQD-V fractal model of the same rock quality. Correlation between results of the fractal and the geological models illustrates that the excellent rocks are associated with porphyric quartz diorite (PQD) units. The results reveal that there is a multifractal nature in rock characterisation with respect to RQD for the Kahang deposit. The proposed fractal model can be intended for the better understanding of the rock quality for purpose of determination of the final pit slope.