Product catalogue
High resolution conductivity mapping using regional AEM survey and machine learning
Improvements in discovery and management of minerals, energy and groundwater resources are spurred along by advancements in surface and subsurface imaging of the Earth. Over the last half decade Australia has led the world in the collection of regionally extensive airborne electromagnetic (AEM) data coverage, which provides new constraints on subsurface conductivity structure. Inferring geology and hydrology from conductivity is non-trivial as the conductivity response of earth materials is non-unique, but careful calibration and interpretation does provide significant insights into the subsurface. To date utility of this new data is limited by its spatial extent. The AusAEM survey provides conductivity constraints every 12.5 m along flight lines with no constraints across vast areas between flight lines spaced 20 km apart. Here we provide a means to infer the conductivity between flight lines as an interim measure before infill surveys can be undertaken. We use a gradient boosted tree machine learning algorithm to discover relationships between AEM conductivity models across northern Australia and other national data coverages for three depth ranges: 0–0.5 m, 9–11 m and 22–27 m. The predictive power of our models decreases with depth but they are nevertheless consistent with our knowledge of geological, landscape evolution and climatic processes and an improvement on standard interpolation methods such as kriging. Our models provide a novel complementary methodology to gridding/interpolating from AEM conductivity alone for use by the mining, energy and natural resource management sectors.
<b>Citation: </b>Wilford J., Ley-Cooper Y., Basak S., & Czarnota K., 2022. High resolution conductivity mapping using regional AEM survey and machine learning. In: Czarnota, K. (ed.) Exploring for the Future: Extended Abstracts, Geoscience Australia, Canberra, https://dx.doi.org/10.26186/146380.
Simple
Identification info
- Date (Creation)
- 2022-03-10
- Date (Publication)
- 2022-03-10T23:42:05
- Date (Revision)
- 2022-08-07T23:01:41
- Citation identifier
- Geoscience Australia Persistent Identifier/https://pid.geoscience.gov.au/dataset/ga/146380
- Citation identifier
- Digital Object Identifier/https://dx.doi.org/10.26186/146380
- Cited responsible party
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Role Organisation / Individual Name Details Author Wilford, J.
MEG Internal Contact Author LeyCooper, Y.
MEG Internal Contact Author Basak, S.
Space Division Internal Contact Author Czarnota, K.
MEG Internal Contact Publisher Commonwealth of Australia (Geoscience Australia)
Voice
- Purpose
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High resolution conductivity mapping using regional AEM survey and machine learning- Extended abstract
- Status
- Completed
- Spatial representation type
Extent
Extent
))
- Maintenance and update frequency
- As needed
Resource format
- Title
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Product data repository: Various Formats
- Website
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Data Store directory containing the digital product files
Data Store directory containing one or more files, possibly in a variety of formats, accessible to Geoscience Australia staff only for internal purposes
- Discipline
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remote sensing
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- Discipline
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geophysics
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- theme.ANZRC Fields of Research.rdf
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EARTH SCIENCES
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- Discipline
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AEM
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- Keywords
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Conductivity
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- Discipline
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machine learning
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- Project
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Exploring for the Future
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- Project
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EFTF
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- Keywords
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Australia's Resources Framework
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- Keywords
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Published_External
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Resource constraints
- Title
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Creative Commons Attribution 4.0 International Licence
- Alternate title
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CC-BY
- Edition
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4.0
- Access constraints
- License
- Use constraints
- License
Resource constraints
- Classification
- Unclassified
Associated resource
- Association Type
- Was informed by
- Title
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High resolution conductivity mapping using regional AEM survey and machine learning.
- Citation identifier
- 146163
- Citation identifier
- 8df7fe67-1d3d-4881-8cf5-fa00f141ebd1
- Language
- English
- Character encoding
- UTF8
Distribution Information
- Distributor contact
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Role Organisation / Individual Name Details Distributor Commonwealth of Australia (Geoscience Australia)
Voice
- OnLine resource
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Extended Abstract for download (pdf) [3.4 MB]
Extended Abstract for download (pdf) [3.4 MB]
- Distribution format
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pdf
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Resource lineage
- Statement
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This publication was produced as part of Geoscience Australia's Exploring for the Future Program. It was presented at the Exploring for the Future 2022 Showcase.
- Hierarchy level
- Document
Metadata constraints
- Classification
- Unclassified
Metadata
- Metadata identifier
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urn:uuid/7de740bd-16cb-4dc4-9c7b-8f714962c688
- Title
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GeoNetwork UUID
Type of resource
- Resource scope
- Document
- Name
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GA publication: Extended Abstract
Alternative metadata reference
- Title
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Geoscience Australia - short identifier for metadata record with
uuid
- Citation identifier
- eCatId/146380
- Metadata linkage
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https://ecat.ga.gov.au:8080/geonetwork/srv/eng//metadata/add5bc51-dd4d-408c-8c1b-deebaacf6efe
- Metadata linkage
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https://ecat.ga.gov.au/geonetwork/srv/eng//metadata/d0b9c198-59fa-4db2-9486-a1dabb91549b
- Date info (Creation)
- 2018-05-04T03:37:56
- Date info (Revision)
- 2018-05-04T03:38:12
Metadata standard
- Title
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AU/NZS ISO 19115-1:2014
Metadata standard
- Title
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ISO 19115-1:2014
Metadata standard
- Title
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ISO 19115-3 (Draft Schemas 2015)
- Edition date
- 2015-07-01T00:00:00
- Title
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Geoscience Australia Community Metadata Profile of ISO 19115-1:2014
- Edition
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Version 2.0, April 2015