期刊
ECONOMIC GEOLOGY
卷 116, 期 4, 页码 803-819出版社
SOC ECONOMIC GEOLOGISTS, INC
DOI: 10.5382/econgeo.4803
关键词
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资金
- Barrick Gold Exploration Inc.
- University of Waikato Doctoral Scholarship program
This study utilized micro-X-ray fluorescence (μXRF) and linear programming (LP) to determine mineral distributions and abundances in drill core samples from Carlin-type gold deposits. The results showed that μXRF data analysis can provide accurate mineralogical structures, abundances, and textures. By comparing results from different methods and standards, the study demonstrates the significance of μXRF technology in mineralogical studies of fine-grained sedimentary rocks.
Mineral distributions can be determined in drill core samples from a Carlin-type gold deposit, using micro-X-ray fluorescence (mu XRF) raster data. Micro-XRF data were collected using a Bruker Tornado mu XRF scanner on split drill core samples (similar to 25 x 8 cm) with data collected at a spatial resolution of similar to 100 mu m. Bruker AMICS software was used to identify mineral species from mu XRF 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 mu XRF data. Quantification of mu XRF 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 mu XRF spectra was precise (R-2 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 mu XRF 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 mu XRF 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 transferable 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.
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