Numerous orogenic gold deposits have been discovered within the Archean Abitibi greenstone belt of Canada. These include the Francoeur, Wasamac, Astoria, Zulapa, Goldex, Lamaque, Lac Herbin, and Beaufor deposits, all of which are located within the Cadillac-Larder Lake Fault Zone (CLLFZ). These gold deposits are hosted by various lithologies and vary in terms of style of mineralization, sulfide abundance, and hydrothermal alteration. These variations mean that exploration for new deposits has been difficult in this area using common exploration criteria. This study presents the results of a principal component analysis (PCA)-based approach, combining geochemical and mineralogical data to quickly identify different types of gold mineralization within the CLLFZ, including assessing the use of this approach in mineral exploration.

The first principal components in both classification methods used during this study (PC(E)1 and PC(M)1, representing element geochemical and mineralogical classification respectively) can efficiently discriminate between mineralization and barren/altered rocks. The second principal components (PC(E)2 and PC(M)2) can be used to constrain the host rocks (altered vs. barren) and style of mineralization (disseminated vs. vein-hosted), respectively. Finally, PC(E)3 and PC(M)3 give more detailed information on the nature of the mineralization in an area, possible reflecting variations in the composition of ore-forming fluids. All of the above indicates that the two PCE and PCM classification methods are complementary, which means that using approaches that combine these methods will provide a comprehensive understanding of the nature of studied samples and/or deposits.

Information extracted from the results of the PCA undertaken during this study may be beneficial for mineral exploration in unknown districts, such as glaciated areas, where traditional geological fieldwork is challenging. This study also defines element and mineral mineralization indices based on PC(E)1 and PC(M)1, which enables evaluation of the extent and style of gold mineralization in an area. This study indicates that PCA-based automated mineralogical and geochemical classification methods could be highly useful in exploration for gold deposits.

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