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Record W1972204475 · doi:10.1190/1.1818117

Optimal seismic imaging with curvelets

2003· article· en· W1972204475 on OpenAlexaff
Felix J. Herrmann

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCurveletComputer scienceGeophysical imagingArtificial intelligenceGeologySeismology

Abstract

fetched live from OpenAlex

PreviousNext No AccessSEG Technical Program Expanded Abstracts 2003Optimal seismic imaging with curveletsAuthors: Felix HerrmannFelix HerrmannEOS, University of British Columbiahttps://doi.org/10.1190/1.1818117 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Permalink: https://doi.org/10.1190/1.1818117FiguresReferencesRelatedDetailsCited byCurvelet-based POCS interpolation of nonuniformly sampled seismic recordsJournal of Applied Geophysics, Vol. 79Curvelet-based multiple predictionDaniela Donno, Hervé Chauris, and Mark Noble22 December 2010 | GEOPHYSICS, Vol. 75, No. 6Marine Linear Noise Suppression in the Curvelet DomainCurvelet-Based Noise Attenuation in Prestack Seismic DataSeismic demigration/migration in the curvelet domainHervé Chauris and Truong Nguyen7 February 2008 | GEOPHYSICS, Vol. 73, No. 2Leading-order seismic imaging using curveletsHuub Douma and Maarten V. de Hoop31 October 2007 | GEOPHYSICS, Vol. 72, No. 6Velocity-independent time-domain seismic imaging using local event slopesSergey Fomel30 March 2007 | GEOPHYSICS, Vol. 72, No. 3Seismic imaging in the curvelet domain and its implications for the curvelet designHervé Chauris6 October 2006Towards the seislet transformSergey Fomel6 October 2006Velocity‐independent time‐domain seismic imaging using local event slopesSergey Fomel7 December 2005Application of 2nd generation wavelets to seismic imagingDimitri Bevc, David L. Donoho, and Sergio E. Zarantonello3 January 2005Wave‐character preserving pre‐stack map migration using curveletsHuub Douma and Maarten V. de Hoop3 January 2005Curvelet‐domain multiple elimination with sparseness constraintsFelix J. Herrmann and Eric Verschuur3 January 2005 SEG Technical Program Expanded Abstracts 2003ISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2003 Pages: 2452 publication data© 2003 Copyright © 2003 Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished Online: 03 Jan 2005 CITATION INFORMATION Felix Herrmann, (2003), "Optimal seismic imaging with curvelets," SEG Technical Program Expanded Abstracts : 997-1000. https://doi.org/10.1190/1.1818117 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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.711
Threshold uncertainty score0.997

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)0.0040.000

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 head0.009
GPT teacher head0.198
Teacher spread0.189 · 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 designNot applicable
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

Citations21
Published2003
Admission routes1
Has abstractyes

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