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Plant products or pulverised drillcore samples are screened/cyclosized by the client and then combined into 3 fractions, which cover the maximum distribution of the economic metals. These are weighed and (preferably) assayed. Normal grainsize limits for optical microscopy are down to about 5µm, but in certain favourable cases, a lower limit of 3µm can be achieved (provided the -3µm slimes are removed). The 3 fractions are mounted on one glass slide and a standard polished thin section is prepared. This allows ready identification of ore minerals by reflected light, and of gangue minerals if necessary, by transmitted light (at least in fractions >35µm grainsize). |
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A set number of randomly selected individual grains (normally, 100) in each fraction are then logged. If a specific mineral or set of minerals (e.g. sphalerite and galena) is of particular concern, then only the grains containing these minerals are logged, to improve the count statistics. The remaining grains, containing only the common minerals like pyrite and gangue that have no economic interest, can be ignored. This is useful when assessing loss to tails, or, for the converse situation, contaminants in concentrates (when only those grains containing a contaminant mineral are logged). Each mineral within the grain is identified and an area % visually estimated. Every grain within a size fraction is assumed to be the same diameter and given an equal weight in the summary calculations. The textural style is also logged for each grain by reference to a previously established texture "icon" library. Coloured stylised grain maps are easily produced to provide an immediate pictorial representation of the overall mineralogical makeup. The
final result is a detailed tabulation (in digital
spreadsheet form) of measured mineralogy parameters that can be readily
compared to other samples separated by space (e.g. different plant stream,
or orebody drillhole samples) or time (e.g. last month's results). The mineralogical parameters quantified can be related to actual plant performance measurements and, over time, predictive models developed to permit meaningful budget forecasts of plant performance with future ore feeds. In addition, routine feed mineralogy can permit the correct assessment of plant changes, i.e. was the measured recovery improvement due to the introduced plant changes, or was it due to fortuitous favourable mineralogy? Further statistical analysis of the mineralogical parameters measured can be undertaken to compare size fractions or samples.
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