none 10.1144/geochem2019-031 Geological Society of London Geological Society of London 1881 107647260 42938 2024111903225900477 10.1144 2024-11-19T07:45:53Z 2019-06-14T16:05:17Z 123 Geochemistry: Exploration, Environment, Analysis GEEA 1467-7873 2041-4943 05 2020 05 2020 20 2 E. C. Grunsky Department of Earth & Environmental Sciences, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada China University of Geosciences, Beijing, China https://orcid.org/0000-0003-4521-163X P. de Caritat Geoscience Australia, GPO Box 378, Canberra ACT 2601, Australia Research School of Earth Sciences, The Australian National University, Canberra ACT 2601, Australia https://orcid.org/0000-0002-4185-9124 Multi-element geochemical surveys of rocks, soils, stream/lake/floodplain sediments and regolith are typically carried out at continental, regional and local scales. The chemistry of these materials is defined by their primary mineral assemblages and their subsequent modification by comminution and weathering. Modern geochemical datasets represent a multi-dimensional geochemical space that can be studied using multivariate statistical methods from which patterns reflecting geochemical/geological processes are described (process discovery). These patterns form the basis from which probabilistic predictive maps are created (process validation). Processing geochemical survey data requires a systematic approach to effectively interpret the multi-dimensional data in a meaningful way. Problems that are typically associated with geochemical data include closure, missing values, censoring, merging, levelling different datasets and adequate spatial sample design. Recent developments in advanced multivariate analytics, geospatial analysis and mapping provide an effective framework to analyse and interpret geochemical datasets. Geochemical and geological processes can often be recognized through the use of data discovery procedures such as the application of principal component analysis. Classification and predictive procedures can be used to confirm lithological variability, alteration and mineralization. Geochemical survey data of lake/till sediments from Canada and of floodplain sediments from Australia show that predictive maps of bedrock and regolith processes can be generated. Upscaling a multivariate statistics-based prospectivity analysis for arc-related Cu–Au mineralization from a regional survey in the southern Thomson Orogen in Australia to the continental scale, reveals a number of regions with a similar (or stronger) multivariate response and hence potentially similar (or higher) mineral potential throughout Australia. 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