An algorithm for the three‐dimensional inversion of magnetotelluric data
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Abstract
PreviousNext No AccessSEG Technical Program Expanded Abstracts 2002An algorithm for the three‐dimensional inversion of magnetotelluric dataAuthors: Colin G. FarquharsonDouglas W. OldenburgEldad HaberRoman ShekhtmanColin G. FarquharsonUBC‐Geophysical Inversion Facility, U. of British Columbia, Vancouver, Canada, Douglas W. OldenburgUBC‐Geophysical Inversion Facility, U. of British Columbia, Vancouver, Canada, Eldad HaberEMI‐Schlumberger, Richmond, CA, and Roman ShekhtmanUBC‐GIFhttps://doi.org/10.1190/1.1817336 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InReddit Permalink: https://doi.org/10.1190/1.1817336FiguresReferencesRelatedDetailsCited byHybrid mesh for magnetotelluric forward modeling based on the finite element method11 January 2023 | Scientific Reports, Vol. 13, No. 1Fast 3D simulation of magnetotelluric data in anisotropic media using a rational Krylov methodJunjun Zhou, Ningbo Bai, Xiangyun Hu, Tiaojie Xiao, and Zhidan Long17 October 2023 | GEOPHYSICS, Vol. 88, No. 6Processing of passive EM fields acquired during active-source airborne EM surveys4 February 2021 | Exploration Geophysics, Vol. 52, No. 6An efficient parallel algorithm for 3D magnetotelluric modeling with edge-based finite element6 July 2020 | Computational Geosciences, Vol. 25, No. 1A reduced order approach for probabilistic inversions of 3-D magnetotelluric data I: general formulation1 September 2020 | Geophysical Journal International, Vol. 223, No. 33D inversion of magnetotelluric data by using a hybrid forward-modeling approach and mesh decouplingDeniz Varılsüha11 September 2020 | GEOPHYSICS, Vol. 85, No. 5Subsurface Characterization of the Pennsylvanian Clare Basin, Western Ireland, by Means of Joint Interpretation of Electromagnetic Geophysical Data and Well‐Log Data9 July 2019 | Journal of Geophysical Research: Solid Earth, Vol. 124, No. 7Modeling sferic signals extracted from active-source AEM dataDaniel Sattel and Eric Battig27 August 2018Removal of galvanic distortion effects in 3D magnetotelluric data by an equivalent source techniqueWenwu Tang, Yaoguo Li, Douglas W. Oldenburg, and Jianxin Liu8 February 2018 | GEOPHYSICS, Vol. 83, No. 2The advantages of complementing MT profiles in 3-D environments with geomagnetic transfer function and interstation horizontal magnetic transfer function data: results from a synthetic case study23 September 2016 | Geophysical Journal International, Vol. 207, No. 3Integration of controlled-source and radio magnetotellurics, electric resistivity tomography, and reflection seismics to delineate 3D structures of a quick-clay landslide site in southwest of SwedenChunling Shan, Mehrdad Bastani, Alireza Malehmir, Lena Persson, and Emil Lundberg12 January 2016 | GEOPHYSICS, Vol. 81, No. 13-D inversion of magnetotelluric data using unstructured tetrahedral elements: applicability to data affected by topography29 May 2015 | Geophysical Journal International, Vol. 202, No. 23D marine magnetotelluric modeling and inversion with the finite-difference time-domain methodSébastien de la Kethulle de Ryhove and Rune Mittet8 October 2014 | GEOPHYSICS, Vol. 79, No. 6Magnetotelluric static shift correction using an equivalent source techniqueWenwu Tang, Yaoguo Li, Douglas W. Oldenburg, and Jianxin Liu5 August 2014The inability of magnetotelluric off-diagonal impedance tensor elements to sense oblique conductors in three-dimensional inversion17 December 2013 | Geophysical Journal International, Vol. 196, No. 3Magnetotelluric 3-D inversion—a review of two successful workshops on forward and inversion code testing and comparison14 March 2013 | Geophysical Journal International, Vol. 193, No. 3Methods 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. 3The modeling of ZTEM data with 2D and 3D algorithmsDaniel Sattel and Ken Witherly25 October 2012Large-scale inversion of ZTEM dataElliot Holtham and Douglas W. Oldenburg9 July 2012 | GEOPHYSICS, Vol. 77, No. 4Electrical 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 inversion of MT and ZTEM dataElliot Holtham and Douglas W. Oldenburg21 October 2010Constructing piecewise-constant models in multidimensional minimum-structure inversionsColin G. Farquharson26 December 2007 | GEOPHYSICS, Vol. 73, No. 1Three‐dimensional forward modelling and inversion of Z‐TEM dataElliot Holtham and Douglas W. Oldenburg15 December 2008Constructing piecewise‐constant models in multi‐dimensional minimum‐structure inversionsColin G. Farquharson6 October 2006Three-Dimensional Electromagnetic Modelling and Inversion from Theory to ApplicationSurveys in Geophysics, Vol. 26, No. 6Three‐dimensional inversion of MT data from the Turquoise Ridge mine, NevadaColin G. Farquharson, Douglas W. Oldenburg, and Peter Kowalczyk3 January 2005 SEG Technical Program Expanded Abstracts 2002 ISSN (print):1052-3812 ISSN (online):1949-4645 Copyright: 2002 Pages: 2478 publication data© 2002 Copyright © 2002 Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished Online: 03 Jan 2005 CITATION INFORMATION Colin G. Farquharson, Douglas W. Oldenburg, Eldad Haber, and Roman Shekhtman, (2002), "An algorithm for the three‐dimensional inversion of magnetotelluric data," SEG Technical Program Expanded Abstracts : 649-652. https://doi.org/10.1190/1.1817336 Plain-Language Summary PDF DownloadLoading ...
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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) | 0.005 | 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 it