Abstract
A previous study demonstrated the theoretical development of a model for assessing bulk ore sortability. However, the model has not been validated with many cases. In this study, the developed model was validated using the production data from 232 draw points in a block cave copper mine. For each draw point, sorting results and mine economics were predicted using fractal modelling and compared with results based on actual data analysis. The statistical error was measured for the fractal model predictions of feed grade, mass yield, pre-concentrate grade, metal recovery, and NSR with and without bulk ore sorting. An optimised approach was developed using multifractal modelling; two sets of fractal parameters were determined to characterise the metal distribution in high- and low-grade ranges. The results showed that the multifractal model was more accurate than the fractal model in predicting the sorting results and assessing ore sortability.
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