3‐D magnetotelluric inversion for resource exploration
Bibliographic record
Abstract
PreviousNext No AccessSEG Technical Program Expanded Abstracts 20013‐D magnetotelluric inversion for resource explorationAuthors: Randall L. MackieWilliam RodiM. Donald WattsRandall L. MackieGSY‐USA, Inc., William RodiMassachusetts Institute of Technology, and M. Donald WattsGeosystem srlhttps://doi.org/10.1190/1.1816392 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InReddit Permalink: https://doi.org/10.1190/1.1816392FiguresReferencesRelatedDetailsCited by3D Step-by-step inversion strategy for audio magnetotellurics data based on unstructured mesh17 February 2022 | Applied Geophysics, Vol. 18, No. 3Three‐dimensional electrical structure of the northwestern margin of the Karamay region, China, revealed by magnetotelluric data14 September 2020 | Geophysical Prospecting, Vol. 68, No. 9Three-dimensional electrical conductivity in the mantle beneath the Payún Matrú Volcanic Field in the Andean backarc of Argentina near 36.5°S: evidence for decapitation of a mantle plume by resurgent upper mantle shear during slab steepening25 June 2014 | Geophysical Journal International, Vol. 198, No. 2NLCG and L-BFGS optimization for 3D HEM inversionYunhe Liu and Changchun Yin19 August 2013Methods and algorithms for reconstructing three-dimensional distributions of electric conductivity and polarization in the medium by finite-element 3D modeling using the data of electromagnetic sounding8 May 2013 | Izvestiya, Physics of the Solid Earth, Vol. 49, No. 3Multiple-domain, simultaneous joint inversion of geophysical data with application to subsalt imagingMichele De Stefano, Federico Golfré Andreasi, Simone Re, Massimo Virgilio, and Fred F. Snyder5 May 2011 | GEOPHYSICS, Vol. 76, No. 3A compressed implicit Jacobian scheme for 3D electromagnetic data inversionMaokun Li, Aria Abubakar, Jianguo Liu, Guangdong Pan, and Tarek M. Habashy28 April 2011 | GEOPHYSICS, Vol. 76, No. 3Electrical resistivity structure at the northern margin of the Tibetan Plateau and tectonic implications7 December 2011 | Journal of Geophysical Research, Vol. 116, No. B12Application of the 3D magnetotelluric inversion code in a geologically complex area9 June 2010 | Geophysical Prospecting, Vol. 58, No. 6Three‐dimensional regularized Gauss‐Newton inversion algorithm using a compressed implicit Jacobian calculation for electromagnetic applicationsMaokun Li, Aria Abubakar, Jianguo Liu, Guangdong Pan, and Tarek M. Habashy21 October 2010Three-dimensional inversion of magnetotelluric data for mineral exploration: An example from the McArthur River uranium deposit, Saskatchewan, CanadaJournal of Applied Geophysics, Vol. 68, No. 43D magnetotelluric inversion using a limited-memory quasi-Newton optimizationDmitry Avdeev and Anna Avdeeva27 April 2009 | GEOPHYSICS, Vol. 74, No. 3Advancing process‐based watershed hydrological research using near‐surface geophysics: a vision for, and review of, electrical and magnetic geophysical methods11 March 2008 | Hydrological Processes, Vol. 22, No. 18A survey of current trends in near-surface electrical and electromagnetic methodsEsben Auken, Louise Pellerin, Niels B. Christensen, and Kurt Sørensen7 September 2006 | GEOPHYSICS, Vol. 71, No. 5Three-Dimensional Electromagnetic Modelling and Inversion from Theory to ApplicationSurveys in Geophysics, Vol. 26, No. 6Mining, Environmental, Petroleum, and Engineering Industry Applications of Electromagnetic Techniques in GeophysicsSurveys in Geophysics, Vol. 26, No. 5Multi-dimensional electromagnetic modeling and inversion with application to near-surface earth investigationsComputers and Electronics in Agriculture, Vol. 46, No. 1-3Accelerated integral equation inversion of 3‐D magnetotelluric data in models with inhomogeneous backgroundNikolay Golubev and Michael S. Zhdanov7 December 20053D inversion of a scalar radio magnetotelluric field data setGregory A. Newman, Stephan Recher, Bülent Tezkan, and Fritz M. Neubauer29 May 2003 | GEOPHYSICS, Vol. 68, No. 32-D and 3-D interpretation of magnetotelluric data in the Bajawa geothermal field, central Flores, IndonesiaBULLETIN OF THE GEOLOGICAL SURVEY OF JAPAN, Vol. 53, No. 2-3 SEG Technical Program Expanded Abstracts 2001ISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2001 Pages: 2135 publication data© 2001 Copyright © 2001 Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished Online: 03 Jan 2005 CITATION INFORMATION Randall L. Mackie, William Rodi, and M. Donald Watts, (2001), "3‐D magnetotelluric inversion for resource exploration," SEG Technical Program Expanded Abstracts : 1501-1504. https://doi.org/10.1190/1.1816392 Plain-Language Summary PDF DownloadLoading ...
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".