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Estimating mineralogy in bulk samples
Citation
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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Official URL: https://www.ausimm.com.au/publications/epublicatio...
Abstract
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 |
Downloads: | 163 View Download Statistics |
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