New Research Initiatives in Geometallurgical Integration û Moving Towards a Common Operating Language

The emerging discipline of ægeometallurgyÆ is not new but is becoming increasingly recognised as a discrete and high-value activity that reflects an ongoing commercial and cultural trend towards more effective mine site integration and optimisation. Geometallurgy involves a quantified and spatially constrained approach to ore characterisation in terms of relationships to critical processing performance. Industry recognition of the need for large-scale, integrated geometallurgical research is currently supporting a major new research initiative. The AMIRA International P843 æGeMIIIÆ project (geometallurgical mapping and mine modelling) is a cross discipline collaboration involving four major Australian research groups; CODES the ARC Centre of Excellence in Ore Deposits at the University of Tasmania, a world leader in economic geology-related research; the Julius Kruttschnitt Mineral Research Centre (JKMRC) at the University of Queensland, a world leader in mining and mineral processing research; the WH Bryan Mining Geology Research Centre (BRC) at the University of Queensland, which aims to be a world leader in mining geostatistics, operations research and optimisation in mine design and planning; and CSIRO Exploration and Mining in the area of automated core logging. The project is currently supported by 19 global mineral companies. The project aims to deliver fundamental knowledge, tools and methods for more effective approaches to geometallurgical definition of mineralogy, element deportment and texture that can be linked to mineral processing performance and efficiency at a range of scales. Outcomes are improved predictive indices of processing performance that can be embedded in resource block models to define processing domains, which can be exploited in mine planning and optimisation. To achieve these aims the project is involved in a range of technology developments that include more automated core logging technologies, new applications of automated microscopy and development of software-based texture analysis and categorisation techniques. Attributes derived from these measurement technologies are used to develop predictive processing models linked to new small-scale physical testing regimes.