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Record W2331858031 · doi:10.1190/1.3627555

An accurate and stable wave equation for pure acoustic TTI modeling

2011· article· en· W2331858031 on OpenAlexaff
Chunlei Chu, Brian K. Macy, Phil D. Anno

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsConocoPhillips (Canada)
FundersConocoPhillips
KeywordsAcoustic wave equationComputer scienceWave equationAcousticsAcoustic wavePhysicsMathematical analysisMathematics

Abstract

fetched live from OpenAlex

One fundamental shortcoming of the conventional pseudo-acoustic approximation is that it only prevents shear wave propagation along the symmetry axis of anisotropy and not in other directions. This problem leads to the presence of unwanted shear waves in P-wave simulation results and brings artifacts into P-wave RTM images. More significantly, the pseudo-acoustic wave equations become unstable for anisotropy parameters ε < δ and for heterogeneous models with highly varying dip and azimuth angles in tilted transversely isotropic (TTI) media. Pure acoustic anisotropic wave equations completely de-couple the P-wave response from the elastic wavefleld and naturally solve all the above-mentioned problems. In this work, we propose a new pure acoustic TTI wave equation and compare it with the conventional coupled pseudo-acoustic wave equation. We derive finite difference solutions to this new equation and use numerical examples to demonstrate that it produces highly accurate P-wave results, very close to results produced by coupled pseudo-acoustic wave equations, but completely free from shear wave artifacts.

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)0.000
metaresearch head score (Gemma)0.002
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.101
GPT teacher head0.247
Teacher spread0.146 · 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

Citations7
Published2011
Admission routes1
Has abstractyes

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