Brief description
As part of Geoscience Australia’s Exploring for the Future Program, Broadband and Audio Magnetotelluric (MT) data were acquired at 131 stations in the East Tennant region, Northern Territory, in 2019. This survey aimed to characterise major crustal structures, to map cover thickness to assist in stratigraphic drill targeting, and to help understand mineral potential in the region. The data package was released in December 2019 (http://dx.doi.org/10.26186/5df80d8615367) and the 3D resistivity model was released in March 2020 (https://pid.geoscience.gov.au/dataset/ga/135011). We applied a probabilistic approach to inverting high-frequency MT data for cover thickness estimation using the 1D Rj-McMCMT code, newly developed in Geoscience Australia. 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 algorithm uses trans-dimensional Markov chain Monte Carlo techniques to solve for a probabilistic resistivity-depth model. Once the ensemble of models is generated, its statistics are analysed to assess the posterior probability distribution of the resistivity at any particular depth, as well as the number of layers and the depths of the interfaces. This stochastic approach gives a thorough exploration of the model space and a more robust estimation of uncertainty than deterministic methods allow. This release package includes the results of probabilistic inversion of Audio Magnetotelluric data at the 131 stations. They can be used to estimate cover thickness for drill site planning, and to map the base of geological basins in the region. Model data files are large, but can be made available on request to clientservices@ga.gov.au.Lineage
Maintenance and Update Frequency: asNeededIssued: 23 09 2020
text: westlimit=135.00; southlimit=-20.20; eastlimit=137.00; northlimit=-18.60
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Download model results (pdf) [265.6 MB]
uri :
https://d28rz98at9flks.cloudfront.net/144339/144339_00_0.zip
Readme file (txt) [3.0 KB]
uri :
https://d28rz98at9flks.cloudfront.net/144339/144339_01_0.txt
- DOI : 10.26186/144339
- URI : pid.geoscience.gov.au/dataset/ga/144339
- global : 0ed8959a-0e59-489d-ad88-2035aa9ce64b