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Estimating mineralogy in bulk samples


Berry, RF and Hunt, JA and McKnight, SW, Estimating mineralogy in bulk samples, Proceedings of the 1st International Geometallurgy Conference (GeoMet 2011), 05-07 September 2011, Brisbane, pp. 153-156. ISBN 9781921522499 (2011) [Refereed Conference Paper]

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This report looks at two ways to estimate the bulk mineralogy of the rocks for assay intervals. The aim is to find an efficient indicator of the most common minerals in the rock. Phase (modal) analysis has traditionally been done using visual methods such as point counting and image analysis. A modern version of this process is the X-ray point counting routine using the SEM-EDS based software. These methods are too slow and expensive for routine analysis of bulk sample mineralogy at the normal assay spacing. Two sources of data were considered that provide information that can be used to determine the mineral abundance in assay samples. The most widely applied method is (semi-) quantitative X-ray diffraction (QXRD). The QXRD method is most applicable to major minerals and has limited application to minerals at low abundance. The nominal detection limit is 0.5%. Values below 5% have large errors. A second, less common, method is calculation of mineralogy from chemical assay data. Conversion of chemical analyses to mineralogical analyses depends on the unique chemical composition of each mineral. Elements only found in one mineral are easily accounted for, but many compositions are ambiguous. Deciding on the actual mineralogy is not simple. Recalculation of mineral mode from chemical analyses is more accurate than QXRD when the correct minerals, and mineral compositions, are known. Where only a few QXRD analyses are available they can be used to setup a standard for calculation of mineralogy from assay data. We found linear programming works well in this environment. The best results are obtained when both H2O and CO2 are directly measured. LOI should be included if these are not available. Where both QXRD and chemical analysis are available for all samples, the best results are obtained using the least squared method to merge the datasets assuming QXRD errors have much higher analytical errors than chemical assays. The combined method provides more robust results because the high abundance minerals are controlled by the QXRD measurements while the chemical assays improve the precision for low abundance minerals.

Item Details

Item Type:Refereed Conference Paper
Keywords:calculated mineralogy
Research Division:Earth Sciences
Research Group:Geology
Research Field:Resource geoscience
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in the earth sciences
UTAS Author:Berry, RF (Associate Professor Ron Berry)
UTAS Author:Hunt, JA (Dr Julie Hunt)
ID Code:117187
Year Published:2011
Funding Support:Australian Research Council (CE0561595)
Deposited By:CODES ARC
Deposited On:2017-06-01
Last Modified:2017-10-24
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