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 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.

中文翻译：

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钻芯表面的定量矿物制图I：一种微米XRF矿物计算方法，以及一种来自卡林型金矿床的热液蚀变，细粒沉积岩的制图方法

可以使用微X射线荧光（µXRF）栅格数据确定来自Carlin型金矿床的钻芯样品中的矿物分布。使用Bruker Tornado µXRF扫描仪在分开的钻芯样品（约25×8 cm）上收集Micro-XRF数据，并以约100 µm的空间分辨率收集数据。使用布鲁克AMICS软件从µXRF栅格数据中识别矿物种类，该数据表明由于样品的细粒度性质，许多单独的样品点都是矿物混合物。为了估算每个像素中的矿物质丰度，我们对量化的µXRF数据使用了线性规划（LP）方法。µXRF光谱的定量使用基本参数（FP）无标准方法完成。^2个值在0.98-0.97之间），尽管FP方法给出的铁和钾含量略高，而Mg的含量却低估了。在使用LP计算矿物学之前，通过使用WDS-XRF数据作为校准校正，可进一步提高定量µXRF化学结果的准确性。使用从相同钻芯样品粉末中收集的X射线衍射（XRD）图，将LP矿物的丰度预测与Rietveld精炼结果进行了比较。与定量XRD结果相比，LP预测的矿物学的均方根误差（RMSE）在石英，钾长石，黄铁矿，高岭石，方解石，白云石和伊利石的范围为0.91至7.15％。用于确定矿物学，矿物质丰度，与卡林型金矿床相关的细颗粒沉积岩肉眼看不到的矿物学和矿物结构。这种方法可转移到任何矿石矿床，但在沉积型矿床中特别有用，在这些矿床中，矿石和脉石矿物通常是细粒的，并且难以在手标本中区分。