Document Type
Journal Article
Publication Title
Minerals
Volume
12
Issue
7
Publisher
MDPI
School
School of Science
RAS ID
52743
Funders
Deep Earth Imaging Future Science Platform and Mineral Resources Discovery Program at CSIRO
Abstract
The ferricrete units (Fe oxide cemented colluvial-alluvial sediment) of the Yilgarn Craton in Western Australia formed during the humid tropical and sub-tropical climates of the Cenozoic. Ferricretes are generally developed on long-lived paleodrainage systems and are products of the ferruginisation of detritus provided by the continuous erosion of upslopes. These iron-rich accumulations can become Au-enriched, as is the case in several locations previously discovered in the Yilgarn Craton; many of these host economic secondary gold deposits (e.g., Moolart Well, Mt Gibson, and Bulchina), typically occurring downslope of low saprolite hills and near paleovalleys (i.e., inset-valleys). Inset-valleys are a common paleotopographic feature buried under Quaternary alluvial and colluvial sedimentary cover. Maps of these ancient channel networks can be used as a proxy for targeting ferricrete gold deposits. These inset-valley systems generally form dendritic and noisy patterns in high-resolution aeromagnetic data due to the presence of maghemite-rich nodules and detrital magnetic pisoliths on their flanks. The main aim of this study was to use high-resolution aeromagnetic data to target ferricrete units related to inset-valleys systems across the Yilgarn Craton. A spatial predictive model was used to learn and predict the geological units of interest from pre-processed aeromagnetic data. The predicted inset-valleys systems were able to confine the exploration space and define a new exploration frontier for ferricrete gold deposits.
DOI
10.3390/min12070879
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Comments
Talebi, H., Markov, J., Salama, W., Otto, A., Metelka, V., Anand, R., & Cole, D. (2022). Targeting paleovalley-related ferricrete units in yilgarn craton using high-resolution aeromagnetic data and spatial machine learning. Minerals, 12(7), 879. https://doi.org/10.3390/min12070879