Hood, SB and Cracknell, MJ, Relating altered rocks to equivalent protoliths using clustering and classification of geochemical data at the Minto copper-gold mine, Yukon, Canada, SEG 2017 Ore Deposits of Asia: China and Beyond Programme, 17-20 September 2017, Beijing, China (2017) [Non Refereed Conference Paper]
Here we present a workflow to process a whole rock geochemical dataset and produce labels for groups of similar least-altered protolith rocks, and then apply these labels to groups of altered rocks. Protolith samples were clustered using K-Means, a technique that involves partitioning n observations into K clusters such that each sample is associated to the cluster belonging to the nearest mean. This clustering approach is analogous to visually assigning samples to groups based on X-Y geochemical plots, e.g., granite AFM diagrams that geologists commonly use. The advantage of K-Means clustering is that many variables can be considered simultaneously. Altered samples were classified using Random Forests, a supervised classification algorithm, based on the cluster results for the protoliths groups.
This approach allows the rapid association of altered samples to their likely corresponding protolith. Interpreting the results gives insight into original protolith geometry, and undertaking further processing can improve the understanding of chemical changes during alteration. Generating and spatially interpreting results took only a few hours, including QaQc and trialling different pre-processing approaches, and was completed without costly geochemical software. Cross section interpretations of protolith geometry, i.e., before ore deposit formation, has an added benefit of lithology label confidence measures from Random Forests.
The motivation of this workflow is to assist geologists working with large drillhole datasets including geochemical information and manual logging information. A common task during exploration is to provide interpretations of site geology, and information about the effects and spatial extent of alteration related to mineralisation. These, in turn, give exploration and mining teams a basis for understanding the potential role of original rock geometry controls on the location of ore, or hallmarks of enveloping alteration zones. The aim of this workflow is to provide a high-speed approach to processing drillhole information that is reproducible and objective. However, the method is not intended to be a "black box", and carefully selection of samples and consideration of results by a geologist is still required.
|Item Type:||Non Refereed Conference Paper|
|Keywords:||supervised classification, unsupervised clustering, geochemistry|
|Research Division:||Earth Sciences|
|Research Field:||Geochemistry not elsewhere classified|
|Objective Division:||Mineral Resources (excl. Energy Resources)|
|Objective Group:||Mineral Exploration|
|Objective Field:||Mineral Exploration not elsewhere classified|
|UTAS Author:||Hood, SB (Mr Shawn Hood)|
|UTAS Author:||Cracknell, MJ (Dr Matthew Cracknell)|
|Deposited By:||CODES ARC|
|Downloads:||2 View Download Statistics|
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