Material fingerprinting as a potential tool to domain orebody hardness and enhancing the prediction of work index

Material fingerprinting as a potential tool to domain orebody hardness and enhancing the prediction of work index

van Duijvenbode, J.R. (TU Delft Resource Engineering)
Cloete, L. M. (AngloGold Ashanti South Africa, Johannesburg)
Soleymani Shishvan, M. (TU Delft Resource Engineering)
Buxton, M.W.N. (TU Delft Resource Engineering)

2021

Geochemical and mineralogical datasets from Tropicana Gold Mine, Australia, have been used to define ore fingerprints. VNIR/SWIR spectral data were represented by four normalised wavelength regions and were clustered to form spectral classes. Sequentially, these spectral class proportions within a block and collocated XRF data were clustered to from material types (fingerprints). The material types were related to an Equotip-BWi correlation. These correlations can be used to extrapolate a hardness signature and generate a BWi proxy for different blocks. The combined fingerprints and BWi proxy can assist as a tool for enhancing the prediction of comminution behaviour. They can explain specific domain-related hardness variations. For example, one material type could be separated into a softer (~15-18 kWh/t), and harder (>20 kWh/t) material blend. This was accomplished using the commonly overlooked VNIR region at 605 nm. This outcome has significance for blending strategies.

http://resolver.tudelft.nl/uuid:54ffc11b-6265-46a7-a078-68e273cbc868

The Southern African institute of Mining and Metallurgy

978-1-928410-26-3

Proceedings APCOM 2021

APCOM 2021 Mineral Industry 4.0, 2021-08-30 → 2021-09-01, Virtual event

Institutional Repository

conference paper

© 2021 J.R. van Duijvenbode, L. M. Cloete, M. Soleymani Shishvan, M.W.N. Buxton