A rapid estimation of processing behaviour based on ore texture

TUNGPALAN, NGUYEN A, EVANS, MANLAPIG, NGUYEN K

K Tungpalan1*, A Nguyen2, C Evans1, E Manlapig3, J Jackson4, K Nguyen5

1.W.H. Bryan Mining and Geology Research Centre (BRC), Sustainable Minerals Institute, The University of Queensland, Australia

2.BHP, Australia

3.Sustainable Minerals Institute, The University of Queensland, Australia

4.IMDEX Limited, Australia

5.Consultant, Australia

Presented at Procemin GEOMET 2019

ABSTRACT

Ore texture represents the fundamental ore properties that significantly influence processing behaviour. However, the current measurement to obtain detailed textural information is through the QEMSCAN and MLA, which is expensive and time-consuming.

A method for rapid assessment of processing behaviour based on an assessment of the heterogeneity of ore texture extracted from drill core images was developed. The method involves i) drill core scanning in a hyperspectral scanning device to generate high resolution core images, ii) image processing using texture spectrum analysis and cluster analysis to extract and classify ore texture, and iii) modelling to correlate texture heterogeneity with processing behaviour.

A case study performed on selected drill cores from a copper porphyry deposit demonstrates the application of the method in estimating the comminution parameter A*b for the entire set of drill cores and in predicting the breakage behaviour of the ore. The results indicated a greater degree of variability in breakage, and that the VeryHard group (average A*b of 27) is dominated by the more heterogeneous texture while the Very Soft group (average A*b of 196) is dominated by the more homogeneous texture.

The case study demonstrated the usefulness of the method in providing a rapid and cost-effective approach, which leverages high resolution textural data measured at core-scale to extract information which is relevant to processing with minimal need for physical testwork. The method also allows a semi-automated and rapid evaluation of theprocessing variability of the ores from drill core samples. When incorporated into the block model, the results of this technique can potentially provide a rapid evaluation of the processing variability within the orebody.

ACKNOWLEDGEMENTS

The authors would like to thank Professor Rick Valenta and colleagues at the W.H. Bryan Mining and Geology Research Centre and the Julius Kruttschnitt Mineral Research Centre, Sustainable Minerals Institute, The University of Queensland

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