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Record W2032770106 · doi:10.1190/1.1816583

Constrained three parameter AVO inversion and uncertainty analysis

2001· article· en· W2032770106 on OpenAlexaffabout
Jonathan E. Downton, Laurence R. Lines

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsInversion (geology)Measurement uncertaintyGeologyComputer scienceMathematicsStatisticsSeismology

Abstract

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PreviousNext No AccessSEG Technical Program Expanded Abstracts 2001Constrained three parameter AVO inversion and uncertainty analysisAuthors: Jonathan E. DowntonLaurence R. LinesJonathan E. DowntonScott Pickford / University of Calgary and Laurence R. LinesUniversity of Calgaryhttps://doi.org/10.1190/1.1816583 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Permalink: https://doi.org/10.1190/1.1816583FiguresReferencesRelatedDetailsCited ByBayesian Deterministic Inversion Based on the Exact Reflection Coefficients Equations of Transversely Isotropic Media With a Vertical Symmetry AxisIEEE Transactions on Geoscience and Remote Sensing, Vol. 60Stress prediction and evaluation approach based on azimuthal amplitude‐versus‐offset inversion of unconventional reservoirs3 December 2020 | Geophysical Prospecting, Vol. 69, No. 2The preconditioned ARD-based AVA inversion method for P-impedance and S-impedanceYongzhen Ji, Huafeng Hu, Zhengliang Lin, Kefei Zhang, and Han Zhong30 September 2020Nonlinear amplitude versus angle inversion for transversely isotropic media with vertical symmetry axis using new weak anisotropy approximation equations20 April 2020 | Petroleum Science, Vol. 17, No. 3Matrix-fluid decoupling-based joint PP-PS-wave seismic inversion for fluid identificationBing-Yi Du, Wu-Yang Yang, Jing Zhang, Xue-Shan Yong, Jian-Hu Gao, and Hai-Shan Li19 April 2019 | GEOPHYSICS, Vol. 84, No. 3Three-term amplitude-variation-with-offset projectionsVaughn Ball, Luis Tenorio, Christian Schiøtt, Michelle Thomas, and J. P. Blangy2 August 2018 | GEOPHYSICS, Vol. 83, No. 5Pre-stack seismic density inversion in marine shale reservoirs in the southern Jiaoshiba area, Sichuan Basin, China26 July 2018 | Petroleum Science, Vol. 15, No. 3A nonlinear multiparameter prestack seismic inversion method based on hybrid optimization approach24 January 2018 | Arabian Journal of Geosciences, Vol. 11, No. 3Simultaneous inversion of P- and S-wave impedance based on an improved AVO equationXin Fu, Feng Zhang, and Xiang-Yang Li17 August 2017Target-oriented linear least squares and nonlinear, trust-region Newton inversions of plane waves using AVA and PVA data for elastic model parametersTing Gong and George A. McMechan20 August 2016 | GEOPHYSICS, Vol. 81, No. 5AVO INVERSION WITH THE INVERSE OPERATOR ESTIMATION ALGORITHM1 August 2016 | Chinese Journal of Geophysics, Vol. 59, No. 3Blocky inversion of prestack seismic data using mixed-normsDaniel O. Pérez*, Danilo R. Velis, and Mauricio D. Sacchi5 August 2014High-resolution prestack seismic inversion using a hybrid FISTA least-squares strategyDaniel O. Pérez, Danilo R. Velis, and Mauricio D. Sacchi2 September 2013 | GEOPHYSICS, Vol. 78, No. 5AVO inversion with t-distribution as priori constraintQichao Zhou, Xingyao Yin, Zhaoyun Zong, and Hanqing Liu19 August 2013Elastic impedance variation with angle inversion for elastic parameters27 March 2012 | Journal of Geophysics and Engineering, Vol. 9, No. 3Deterministic mapping of reservoir heterogeneity in Athabasca oil sands using surface seismic dataYong Xu and Satinder Chopra15 December 2008A novel prestack AVO inversion and its applicationXingyao Yin, Peijie Yang, and Guangzhi Zhang15 December 2008Linearized amplitude variation with offset (AVO) inversion with supercritical anglesJonathan E. Downton and Charles Ursenbach28 August 2006 | GEOPHYSICS, Vol. 71, No. 5Wide‐angle inversion for density: Tests for heavy‐oil reservoir characterizationBaishali Roy, Phil Anno, and Michael Gurch6 October 2006A study on applicability of density inversion in defining reservoirsYongyi Li7 December 2005Three term AVO waveform inversionJonathan E. Downton and Laurence R. Lines3 January 2005Spherical wave AVO modeling of converted waves in isotropic mediaArnim B. Haase3 January 2005AVO before NMOJonathan E. Downton and Laurence R. Lines3 January 2005Plane waves, spherical waves and angle‐dependent P‐wave reflectivity in elastic VTI‐modelsArnim B. Haase3 January 2005 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: 03 Jan 2005 CITATION INFORMATION Jonathan E. Downton and Laurence R. Lines, (2001), "Constrained three parameter AVO inversion and uncertainty analysis," SEG Technical Program Expanded Abstracts : 251-254. https://doi.org/10.1190/1.1816583 Plain-Language Summary PDF DownloadLoading ...

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.856
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.017
GPT teacher head0.217
Teacher spread0.200 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations51
Published2001
Admission routes2
Has abstractyes

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