High-Resolution Physical Properties, Geochemistry, and Alteration Mineralogy for the Host Rocks of the Archean Lemoine Auriferous Volcanogenic Massive Sulfide Deposit, Canada

Abstract

Multi-parameter data on drill cores has a range of useful applications for ore deposit modeling and mineral exploration. Density, magnetic susceptibility, eight major elements, seven trace elements (portable X-ray fluorescence, pXRF), five mineral groups (near-infrared spectrometry) and average visible light reflectance were determined on rock cores from several drill holes. These are located near the Archean Lemoine auriferous volcanogenic massive sulfide (VMS) deposit in the Chibougamau mining district, Abitibi Subprovince, Quebec, Canada. This case study focuses on one drill hole in particular which has been recently characterized in detail by conventional methods (laboratory geochemistry, petrography, stable isotopes); this provides validation for the multi-sensor dataset. The best variables and immobile element ratios to distinguish between different lithological units in the multi-parameter data are density, magnetic susceptibility, Ti/Zr, Al/Zr, and Zr/Y. Downhole profiles of these parameters allow the four different felsic units in LEM-37, many of which are visually similar, to be distinguished, and geological contacts to be positioned precisely. Such methods would be even more useful in environments where recognition of primary characteristics is strongly hampered by intense hydrothermal alteration and superimposed deformation or metamorphism. Volcanic and intrusive rocks can be placed on classic diagrams to assign them names and magmatic affinities based on the corrected pXRF data. Downhole profiles of major and trace elements, combined with infrared mineralogy, allow hydrothermal alteration to be characterized, yielding results comparable to those of conventional techniques for the same drill hole, but with a much tighter spacing and within potentially shorter timeframes.

The Influence of Spectral Interferences on Critical Element Determination with Portable X-Ray Fluorescence (pXRF)

“…However, portable XRF spectrometers have proven suitable to detect REEs, Ta, and Nb in phosphates and carbonatites [13][14][15], W, Nb, Ta, La, Ce, and Zr in Sn-W ore-bearing granites [20], Ta and Zr in soil overlying granites [12], and P, Ba, Nb, V, Zr, and Y in various mafic to felsic igneous rocks [7,[21][22][23][24]. Consequently, critical elements can be detected and reliably quantified in geological materials devoid of interfering elements or when enriched.…”

High-resolution gamma ray attenuation density measurements on mining exploration drill cores, including cut cores

“…In the current study, the core moves on a track within a multi-sensor core logger (MSCL), which can also measure the magnetic susceptibility of the core, quantify several chemical elements by energy-dispersive X-ray fluorescence, and characterize mineralogical assemblages by visible light and near infrared spectrometry (Ross et al, 2013(Ross et al, , 2014a(Ross et al, , 2014b(Ross et al, , 2016. The logger, which is contained in a mobile laboratory, can also acquire a high-quality continuous image of the core using a line-scan camera.…”

“…The Marelle quartz feldspar porphyry, for example, occupies a distinct field, and so do the mafic dikes within the Alpha Rhyolite. Where there is overlap, geochemistry can be added for additional discriminating power (Ross et al, 2016;Fresia et al, 2017). For such an application, because the density range is small, it is important to use precise and accurate data.…”

“…Third, these data can be integrated with geochemical and mineralogical data to give constrains on the origin of some ore deposits (e.g. Chu et al, 2015) or help discriminate between different lithologies, study hydrothermal alteration and contribute to a better understanding of the geological setting of ore deposits (e.g., Ross et al, 2013Ross et al, , 2016Fresia et al, 2017).…”

Classification of lithostratigraphic and alteration units from drillhole lithogeochemical data using machine learning: A case study from the Lalor volcanogenic massive sulphide deposit, Snow Lake, Manitoba, Canada

“…One significant challenge in such environments is to differentiate between the protolith signature (e.g., Ross et al, 2014) and the signal specific to the overprinting hydrothermal alteration (i.e. post-depositional geochemical modifications to the protolith signature) (e.g., Ross et al, 2016). Protoliths are finite, spatially and statistically coherent features for the most part, whereas alteration 'units' are gradational and irregular in nature.…”