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143705 - Quantitative mineral mapping of drill core surfaces I - print.pdf (6.1 MB)

Quantitative mineral mapping of drill core surfaces I: a method for µXRF mineral calculation and mapping of hydrothermally altered, fine-grained sedimentary rocks from a Carlin-type gold deposit

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posted on 2023-05-20, 22:24 authored by Barker, RD, Shaun BarkerShaun Barker, Wilson, SA, Stock, ED

Mineral distributions can be determined in drill core samples from a Carlin-type gold deposit, using micro-X-ray fluorescence (µXRF) raster data. Micro-XRF data were collected using a Bruker Tornado µXRF scanner on split drill core samples (∼25 × 8 cm) with data collected at a spatial resolution of ∼100 µm. Bruker AMICS software was used to identify mineral species from µXRF raster data, which revealed that many individual sample spots were mineral mixtures due to the fine-grained nature of the samples. In order to estimate the mineral abundances in each pixel, we used a linear programming (LP) approach on quantified µXRF data. Quantification of µXRF spectra was completed using a fundamental parameters (FP) standardless approach. Results of the FP method compared to standardized wavelength dispersive spectrometry (WDS)-XRF of the same samples showed that the FP method for quantification of µXRF spectra was precise (R2 values of 0.98–0.97) although the FP method gave a slight overestimate of Fe and K and an underestimate of Mg abundance. Accuracy of the quantified µXRF chemistry results was further improved by using the WDS-XRF data as a calibration correction before calculating mineralogy using LP. The LP mineral abundance predictions were compared to Rietveld refinement results using X-ray diffraction (XRD) patterns collected from powders of the same drill core samples. The root mean square error (RMSE) for LP-predicted mineralogy compared to quantitative XRD results ranges from 0.91 to 7.15% for quartz, potassium feldspar, pyrite, kaolinite, calcite, dolomite, and illite.

The approaches outlined here demonstrates that µXRF maps can be used to determine mineralogy, mineral abundances, and mineralogical textures not visible with the naked eye from fine-grained sedimentary rocks associated with Carlin-type Au deposits. This approach is transferrable to any ore deposit, but particularly useful in sedimentary-hosted ore deposits where ore and gangue minerals are often fine grained and difficult to distinguish in hand specimen.


Publication title

Economic Geology and the Bulletin of the Society of Economic Geologists










School of Natural Sciences


Economic Geology Publ Co

Place of publication

5808 South Rapp St, Ste 209, Littleton, USA, Co, 80120-1942

Rights statement

© 2021 Economic Geology. Gold Open Access: This paper is published under the terms of the Creative Commons Attribution 3.0 Unported (CC BY 3.0) license (

Repository Status

  • Open

Socio-economic Objectives

Artificial intelligence; Mining and extraction of precious (noble) metal ores

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