Lithogeochemical Discrimination and Classification of Archean Shales in Volcanic Assemblages of the Western Abitibi Greenstone Belt

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Université d'Ottawa / University of Ottawa

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The Abitibi Greenstone Belt (AGB) hosts world-class base and precious metal deposits and continues to be a primary exploration focus. However, increasing depletion of near-surface deposits requires improved geological models to identify future targets at greater depth. Carbonaceous argillites or black shales are present in most ore-hosting volcanic units throughout the AGB, and they are common hosts for synvolcanic base metal deposits and for orogenic gold. Most of the black shale occurrences are in small volcanosedimentary basins that belong to regionally extensive volcanic complexes. Because they have a strong electromagnetic response many of these rocks are targeted for drilling during exploration. This has resulted in a vast, yet widely underappreciated archive of core and data on shales that may hold valuable information to identify potentially ore-hosting sequences at depth. The study examines the geochemistry of the shales in different settings using machine learning approaches to develop new classification strategies. The study uses a comprehensive lithogeochemical database of over 500 black shale samples from the western AGB to test: i) whether they can be reliably classified according to their sediment source (e.g., felsic versus mafic provenance), and ii) whether machine learning techniques can improve the identification of these underlying geochemical patterns. Multielement correlations characteristic of different source rocks and depositional processes were identified by Principal Component Analysis (PCA) and classified by Random Forest (RF) a machine learning algorithm. PCA differentiates between shales derived from mafic and felsic volcanic source rocks, shale that has been hydrothermally altered (or derived from altered volcanic rocks at their source), and shale that may have been hydrothermally altered after deposition. The results show that the geochemistry of shales can be treated much like that of their source volcanic rocks and a strong relationship exists between major geologic features and different types of shales. In particular, black shales that were deposited in restricted volcanic basins can be distinguished from black shales that are more closely associated with regionally extensive turbidite sequences. This outcome can also improve our understanding of mineral potential, distinguishing between shale lithotypes in settings that commonly host base metal deposits and shale lithotypes in other settings that may host later gold deposits. We identify "orogenic gold-type shales" as mainly felsic-type, derived from eroded arc-like assemblages along major crustal-scale faults where orogenic gold deposits are found. We also identify "VMS-type shales" as mainly mafic-type, deposited in rift basins where base metal deposits formed.

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Shale, Archean, Abitibi Greenstone Belt, Argillite, Geochemistry, Machine learning

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