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Record W2008159339 · doi:10.3997/2214-4609.20140197

A Recipe for Practical Full Waveform Inversion in Anisotropic Media

2014· article· en· W2008159339 on OpenAlexaff
Tariq Alkhalifah, R. E. Plessix

Bibliographic record

VenueProceedings · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Waves and Analysis
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsTransverse isotropyAnisotropyIsotropyAmplitudePhysicsNonlinear systemWavelengthPerturbation (astronomy)Acoustic wave equationInversion (geology)Acoustic waveAcousticsGeologyMathematical analysisOpticsMathematicsSeismology

Abstract

fetched live from OpenAlex

Summary In representing the most common (first-order influence, and gravity induced) acoustic anisotropy, transversely isotropic with a vertical symmetry direction (VTI) medium, with the P-wave normal moveout velocity, delta, and eta, we obtain a perturbation radiation pattern that has limited tradeoff between the parameters. Since delta is weakly resolvable from the kinematics of wave propagation, we can use it to play the role that density plays in improving the data fit for an imperfect physical model that ignores the elastic nature of the Earth. An FWI scheme that starts from diving waves would benefit from representing the acoustic VTI model with the P-wave horizontal velocity, eta, and epsilon. In this representation, the diving waves will help us first resolve the horizontal velocity, and then reflections, if the nonlinearity is properly handled, could help us resolve eta, while epsilon comes at the end to improve the amplitude fit (instead of the density). The model update wavelength for acoustic anisotropic FWI is very much similar to that experienced for the isotropic case.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.031
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0310.015

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 head0.020
GPT teacher head0.233
Teacher spread0.213 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations9
Published2014
Admission routes1
Has abstractyes

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