Product catalogue
Probabilistic Inversion of Audio-frequency Magnetotelluric Data and Application to Cover Thickness Estimation for Mineral Exploration in Australia
We have developed a Bayesian inference algorithm and released open-source code for the 1D inversion of audio-frequency magnetotelluric data. The algorithm uses trans-dimensional Markov chain Monte Carlo to solve for a probabilistic resistivity-depth model. The inversion employs multiple Markov chains in parallel to generate an ensemble of millions of resistivity models that adequately fit the data given the assigned noise levels. The trans-dimensional aspect of the inversion means that the number of layers in the resistivity model is solved for rather than being predetermined. The inversion scheme favours a parsimonious solution, and the acceptance criterion ratio is theoretically derived such that the Markov chain will eventually converge to an ensemble that is a good approximation of the posterior probability density (PPD). Once the ensemble of models is generated, its statistics are analysed to assess the PPD and to quantify model uncertainties. This approach gives a thorough exploration of model space and a more robust estimation of uncertainty than deterministic methods allow.
We demonstrate the application of the method to cover thickness estimation for a number of regional drilling programs. Comparison with borehole results demonstrates that the method is capable of identifying major stratigraphic structures with resistivity contrasts. Our results have assisted with drill site targeting, and have helped to reduce the uncertainty and risk associated with intersecting targeted stratigraphic units in covered terrains. Interpretation of the audio-frequency magnetotelluric data has also improved our understanding of the distribution and geometries of sedimentary basins undercover. From an exploration perspective, mapping sedimentary basins and covered near-surface geological features supports the effective search for mineral deposits in greenfield areas.
<b>Citation: </b>
Wenping Jiang, Ross C. Brodie, Jingming Duan, Ian Roach, Neil Symington, Anandaroop Ray, James Goodwin,
Probabilistic inversion of audio-frequency magnetotelluric data and application to cover thickness estimation for mineral exploration in Australia, <i>Journal of Applied Geophysics</i>, Volume 208, 2023, 104869, ISSN 0926-9851, https://doi.org/10.1016/j.jappgeo.2022.104869.
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Identification info
- Date (Creation)
- 2022-01-04
- Date (Publication)
- 2023-02-06T04:45:13
- Citation identifier
- Geoscience Australia Persistent Identifier/https://pid.geoscience.gov.au/dataset/ga/145419
Identifier
- Codespace
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Digital Obejct Identifier
- Cited responsible party
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Role Organisation / Individual Name Details Author Jiang, W.
MEG Internal Contact Author Brodie, R.
MEG Internal Contact Author Duan, J.
MEG Internal Contact Author Roach, I.
MEG Internal Contact Author Symington, N.
MEG Internal Contact Author Ray, A.
MEG Internal Contact Author Goodwin, J.
MEG Internal Contact Publisher Elsevier Ltd
External Contact
- Name
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Journal of Applied Geohysics
- Issue identification
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Vol 208 January 2023, 104869
- Purpose
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Journal article - submitted to 'Journal of Applied Geophysics'
- Status
- Completed
- Point of contact
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Role Organisation / Individual Name Details Point of contact Commonwealth of Australia (Geoscience Australia)
Voice Point of contact Jiang, W.
MEG Internal Contact Resource provider Minerals, Energy and Groundwater Division
External Contact
- Spatial representation type
- Topic category
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- Geoscientific information
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))
- Maintenance and update frequency
- As needed
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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
- theme.ANZRC Fields of Research.rdf
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GEOPHYSICS
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EARTH SCIENCES
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- Discipline
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Magnetotellurics
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- Sub-Topic Category
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Bayesian
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- Theme
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mineral
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- Keywords
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Published_External
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All rights reserved
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© 2023 Elsevier B.V.
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Australian Government Security ClassificationSystem
- Edition date
- 2018-11-01T00:00:00
- Classification
- Unclassified
- Language
- English
- Character encoding
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Role Organisation / Individual Name Details Distributor Commonwealth of Australia (Geoscience Australia)
Voice
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Link to Journal Article
Link to Journal Article
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- File decompression technique
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nil
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Resource lineage
- Statement
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Article submitted to; Journal of Applied Geophysics; Vol 208, January 2023 104869
Metadata constraints
- Title
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Australian Government Security Classification System
- Edition date
- 2018-11-01T00:00:00
- Classification
- Unclassified
Metadata
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urn:uuid/616c09c6-75c7-40c6-91d7-a67a1c523ddf
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GeoNetwork UUID
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- English
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- UTF8
- Contact
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Role Organisation / Individual Name Details Point of contact Commonwealth of Australia (Geoscience Australia)
Voice Owner Jiang, W
Geoscience Australia Internal Contact Point of contact Jiang, W.
MEG Internal Contact
Type of resource
- Resource scope
- Document
- Name
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Journal Articles and Conference Papers
Alternative metadata reference
- Title
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Geoscience Australia - short identifier for metadata record with
uuid
- Citation identifier
- eCatId/145419
- Date info (Creation)
- 2021-05-13T02:26:17
- Date info (Revision)
- 2021-05-13T02:26:17
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
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Geoscience Australia Community Metadata Profile of ISO 19115-1:2014
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Version 2.0, September 2018
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- https://pid.geoscience.gov.au/dataset/ga/122551