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

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

37 Downloads (Pure)


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.
Original languageEnglish
Title of host publicationProceedings APCOM 2021
PublisherThe Southern African institute of Mining and Metallurgy
Number of pages12
ISBN (Print)978-1-928410-26-3
Publication statusPublished - 2021
EventAPCOM 2021 Mineral Industry 4.0: The next digital transformation in mining - Virtual event
Duration: 30 Aug 20211 Sep 2021


ConferenceAPCOM 2021 Mineral Industry 4.0
Abbreviated titleAPCOM 2021
Internet address

Cite this