Characterization and Bulk Sorting of Cu Porphyry Ores

Proceedings, Vol. Proceedings of the 58th Conference of Metallurgists Hosting Copper 2019, 2019

Bamber, A.S.

Since 2008 rapid advances have been made in technologies for the sensing and sorting of ores, particularly copper, and copper-related ores. Advances include significant increases in the sensitivity and throughput, specifically in the area of bulk sorting. Such advances were not possible without contemporaneous advances in the understanding of copper orebodies, in particular the understanding and quantification of the heterogeneity required within an orebody to support an effective sort, regardless of the technology deployed to do this. This paper covers fundamental knowledge in the characterization of orebodies and their ores for sorting; relationships between measures of heterogeneity and sorting response; the design of bulk sorting systems that can exploit this heterogeneity to add value to copper operations; and, a quantification of the value that can be generated from bulk sorting at a case study mine. INTRODUCTION Society currently puts increasing pressure on industries to move towards cleaner and more efficient means of production, and the mining industry is no exception. Mining additionally faces other factors increasing the pressure to be more efficient: high-grade and easily accessible reserves have become largely depleted, therefore the mined grade at operations across most commodities, including and in particular copper, is decreasing. Additionally, the grade of new discoveries in the sector continues to decrease (Schodde, 2011). Factor in the high capital cost of processing facilities and the low levels of efficiency of current grinding circuits, and the situation for such mines becomes dire. Sorting, by maximizing the amount of ore extracted while simultaneously reducing the waste content in ore delivered to downstream processes (whether simply transport and crushing, or more sophisticated circuits such as grinding and flotation or leaching) has long been of interest to mining operations and projects struggling with low margins (Bamber, 2012). However, until recently sorting technologies that are both cost effective and effective at such high throughputs have not been commercially available.

Keywords: Copper 2019, COM2019