Variability, Prediction and Visualisation


The aim of this project is to explore the means of examining, predicting and visualising variability in ore characteristics and processing responses, as an input to more flexible and lower footprint mining, mineral processing and waste disposal

The mining industry has continued to achieve substantial decreases in production cost through a series of innovations, and through the progressive application of economies of scale.  As operations have increased in size, their environmental, social and governance (ESG) footprint has also increased, contributing strongly to a situation in which a large proportion of the supply of many commodities is now not held back by technical challenges, but rather by ESG barriers.  A potential solution to this challenge is to develop knowledge of orebody variability at a scale that will allow lower tonnage, more flexible, and lower footprint mining and processing.

Through industry-sponsored case studies and internal initiatives, this project will explore:

  • Fundamental links between rock characteristics and processing behaviour
  • Innovative measurement and processing of geoscientific data for improved process prediction
  • Innovative visualisation of massive mine datasets 






UQ School of Information Technology and Electrical Engineering