A velocity analysis procedure for multicomponent data with topographic variations
Bibliographic record
Abstract
We have modified the normal-moveout (NMO) equation for both P-wave and converted-wave (C-wave) data to handle surface elevation changes, and we have implemented this equation in our velocity analysis and NMO correction programs. For the C-wave case, we have also developed a new velocity analysis method that combines NMO correction and common conversion point (CCP) binning with a set of trial γ (Vp/Vs) values, thereby reducing errors introduced by the approximate asymptotic conversion point (ACP) binning method. This procedure has been successfully applied to P-wave and C-wave field data from western Canada and the Colombian Foothills. The benefits are both prestack and poststack. Stacked sections from synthetic and field data that have been processed using these modified equations show better focusing and event continuity. Furthermore, since the events on the moveout-corrected gathers are flatter, longer offsets can be retained for AVO analysis. The improved gathers also enable a more robust residual statics calculation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".