Data

Probabilistic Cover-Basement Interface Map in Cloncurry, Australia

Commonwealth Scientific and Industrial Research Organisation
Seille, Hoel ; Visser, Gerhard ; Markov, Jelena ; Simpson, Janelle
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25919/7wer-yf78&rft.title=Probabilistic Cover-Basement Interface Map in Cloncurry, Australia&rft.identifier=https://doi.org/10.25919/7wer-yf78&rft.publisher=Commonwealth Scientific and Industrial Research Organisation&rft.description=Depth to basement map and associated uncertainty map for the Cloncurry area in Queensland, Australia. This maps were produced using a probabilistic sequential workflow consisting in 1) Bayesian inversion of magnetotelluric data and 2) Bayesian Estimate Fusion of depth to basement estimates coming from magnetotelluric probabilistic models and drill holes. &rft.creator=Seille, Hoel &rft.creator=Visser, Gerhard &rft.creator=Markov, Jelena &rft.creator=Simpson, Janelle &rft.date=2022&rft.edition=v1&rft.coverage=westlimit=140.2085; southlimit=-20.8231; eastlimit=140.7758; northlimit=-20.214399999999998; projection=WGS84&rft_rights=Creative Commons Attribution 4.0 International Licence https://creativecommons.org/licenses/by/4.0/&rft_rights=Data is accessible online and may be reused in accordance with licence conditions&rft_rights=All Rights (including copyright) CSIRO 2022.&rft_subject=Magnetotelluric&rft_subject=Bayesian inversion&rft_subject=Bayesian Estimate Fusion&rft_subject=Electrical and electromagnetic methods in geophysics&rft_subject=Geophysics&rft_subject=EARTH SCIENCES&rft_subject=Geophysics not elsewhere classified&rft.type=dataset&rft.language=English Access the data
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Creative Commons Attribution 4.0 International Licence
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Data is accessible online and may be reused in accordance with licence conditions

All Rights (including copyright) CSIRO 2022.

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Depth to basement map and associated uncertainty map for the Cloncurry area in Queensland, Australia. This maps were produced using a probabilistic sequential workflow consisting in 1) Bayesian inversion of magnetotelluric data and 2) Bayesian Estimate Fusion of depth to basement estimates coming from magnetotelluric probabilistic models and drill holes.

Available: 2022-10-28

Data time period: 2020-02-01 to 2021-06-30

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140.7758,-20.2144 140.7758,-20.8231 140.2085,-20.8231 140.2085,-20.2144 140.7758,-20.2144

140.49215,-20.51875

Subjects
Bayesian Estimate Fusion | Bayesian inversion | Earth Sciences | Electrical and Electromagnetic Methods in Geophysics | Geophysics | Geophysics Not Elsewhere Classified | Magnetotelluric |

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Identifiers
ACN 633 798 857