It is widely accepted that bulk ore sorting could provide a step change in processing of low-grade ores. For this to be achieved a rapid, accurate bulk sensor of grade is required as well as sufficient natural variation of grade in the ore stream. CSIRO trialled a magnetic resonance (MR) sensor capable of measuring chalcopyrite, and by inference total copper grade, on the 1300 t/h Ridgeway portal conveyor. The gauge produced an unprecedented set of data down to a 1 t scale for months at a time. This paper analyses the measured variation and compares it to a simple model derived from the bore core data and mixing within the block cave mine._x000D_
The model of the small-scale (<1000 t) variation is developed using fractal methods which have successfully been used in the past for copper porphyry deposits showing a power law or near power law distribution of copper grade and vein sizes. these fractal distributions have two features highly favourable for segregating ore, a large proportion of low-grade pods and the large-scale spatial clustering of grade. we show the presence of fractal ordering in bore core data at short range in the cadia ridgeway porphyry deposit and measure its persistence in the crushed rock produced by the ridgeway block cave mine over one month. the model is then extended to demonstrate the effect of varying head grade, mixing and pod (or diversion) weight on bulk sorting efficiency._x000d_>
CITATION: Coghill, P J, Miljak, D, McGann, A, 2016. Modelling Grade Variation in Crushed Ore at Cadia Ridgeway and Its Potential Consequences for Bulk Ore Sorting, in Proceedings The Third AusIMM International Geometallurgy Conference (GeoMet) 2016, pp 77-88 (The Australasian Institute of Mining and Metallurgy: Melbourne).