Bibliographic record
Abstract
Propagation of seismic waves in real media is in many respects different from propagation in an ideal solid. Presented here is a method for accommodating absorption and dispersion effects in a migration scheme, in which extrapolation operators that compensate for absorption and dispersion are designed. The algorithm is developed in the frequency–wavenumber domain, and is characterized by simplicity, speed, less dependence on stratum obliquity, and good stabilization. To demonstrate absorption and dispersion in the viscoacoustic medium, we first perform forward modelling, which shows that the amplitude of the wave is decreased, frequency is lower and the phase is influenced when a wave propagates in the viscoacoustic medium. We then perform viscoacoustic and elastic 2D pre-stack depth migrations on the synthetic data. Without consideration of the absorption and dispersion in the elastic pre-stack migration scheme, a geological model cannot be imaged properly. For the viscoacoustic pre-stack depth migration scheme, extrapolation operators could compensate for absorption and dispersion, and a proper image be obtained.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".