State-of-the-art analysis of geochemical data for mineral exploration

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...

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Main Authors: Grunsky, E C, de Caritat, Patrice
Format: Article in Journal/Newspaper
Language:English
Published: Geological Society Publishing House 2022
Subjects:
Online Access:http://hdl.handle.net/1885/275597
https://openresearch-repository.anu.edu.au/bitstream/1885/275597/3/State%20of%20the%20art.pdf.jpg
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spelling ftanucanberra:oai:openresearch-repository.anu.edu.au:1885/275597 2023-05-15T17:10:57+02:00 State-of-the-art analysis of geochemical data for mineral exploration Grunsky, E C de Caritat, Patrice 2022-10-18T04:07:50Z application/pdf http://hdl.handle.net/1885/275597 https://openresearch-repository.anu.edu.au/bitstream/1885/275597/3/State%20of%20the%20art.pdf.jpg en_AU eng Geological Society Publishing House 2041-4943 http://hdl.handle.net/1885/275597 https://openresearch-repository.anu.edu.au/bitstream/1885/275597/3/State%20of%20the%20art.pdf.jpg © 2019 The authors http://creativecommons.org/licenses/by/4.0/ Creative Commons Attribution licence CC-BY Geochemistry: Exploration, Environment, Analysis https://pubs.geoscienceworld.org/geea/article/20/2/217/571599/State-of-the-art-analysis-of-geochemical-data-for geochemistry analytical methods compositional data multivariate analytics process discovery process validation predictive mapping machine learning geospatial coherence Melville Peninsula Nunavut Thomson Region New South Wales Journal article 2022 ftanucanberra 2022-10-24T22:15:28Z 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. The National Geochemical Survey of Australia project was supported by Commonwealth funding ... Article in Journal/Newspaper Melville Peninsula Nunavut Australian National University: ANU Digital Collections Canada Melville Peninsula ENVELOPE(-83.999,-83.999,68.001,68.001) Nunavut
institution Open Polar
collection Australian National University: ANU Digital Collections
op_collection_id ftanucanberra
language English
topic geochemistry
analytical methods
compositional data
multivariate analytics
process discovery
process validation
predictive mapping
machine learning
geospatial coherence
Melville Peninsula
Nunavut
Thomson Region
New South Wales
spellingShingle geochemistry
analytical methods
compositional data
multivariate analytics
process discovery
process validation
predictive mapping
machine learning
geospatial coherence
Melville Peninsula
Nunavut
Thomson Region
New South Wales
Grunsky, E C
de Caritat, Patrice
State-of-the-art analysis of geochemical data for mineral exploration
topic_facet geochemistry
analytical methods
compositional data
multivariate analytics
process discovery
process validation
predictive mapping
machine learning
geospatial coherence
Melville Peninsula
Nunavut
Thomson Region
New South Wales
description 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. The National Geochemical Survey of Australia project was supported by Commonwealth funding ...
format Article in Journal/Newspaper
author Grunsky, E C
de Caritat, Patrice
author_facet Grunsky, E C
de Caritat, Patrice
author_sort Grunsky, E C
title State-of-the-art analysis of geochemical data for mineral exploration
title_short State-of-the-art analysis of geochemical data for mineral exploration
title_full State-of-the-art analysis of geochemical data for mineral exploration
title_fullStr State-of-the-art analysis of geochemical data for mineral exploration
title_full_unstemmed State-of-the-art analysis of geochemical data for mineral exploration
title_sort state-of-the-art analysis of geochemical data for mineral exploration
publisher Geological Society Publishing House
publishDate 2022
url http://hdl.handle.net/1885/275597
https://openresearch-repository.anu.edu.au/bitstream/1885/275597/3/State%20of%20the%20art.pdf.jpg
long_lat ENVELOPE(-83.999,-83.999,68.001,68.001)
geographic Canada
Melville Peninsula
Nunavut
geographic_facet Canada
Melville Peninsula
Nunavut
genre Melville Peninsula
Nunavut
genre_facet Melville Peninsula
Nunavut
op_source Geochemistry: Exploration, Environment, Analysis
https://pubs.geoscienceworld.org/geea/article/20/2/217/571599/State-of-the-art-analysis-of-geochemical-data-for
op_relation 2041-4943
http://hdl.handle.net/1885/275597
https://openresearch-repository.anu.edu.au/bitstream/1885/275597/3/State%20of%20the%20art.pdf.jpg
op_rights © 2019 The authors
http://creativecommons.org/licenses/by/4.0/
Creative Commons Attribution licence
op_rightsnorm CC-BY
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