Application of waveform tomography to marine seismic reflection data from the Queen Charlotte Basin of western Canada
Bibliographic record
Abstract
Abstract To obtain a higher resolution quantitative P-wave velocity model, 2D waveform tomography was applied to seismic reflection data from the Queen Charlotte sedimentary basin off the west coast of Canada. The forward modeling and inversion were implemented in the frequency domain using the visco-acoustic wave equation. Field data preconditioning consisted of F-K filtering, 2D amplitude scaling, shot-to-shot amplitude balancing, and time windowing. The field data were inverted between 7 and 13.66 Hz, with attenuation introduced for frequencies miss data to improve the final velocity model; two different approaches to sampling the frequencies were evaluated. The limited maximum offset of the marine data (3770 m) and the relatively high starting frequency (7 Hz) were the main challenges encountered during the inversion. An inversion strategy that successively recovered shallow-to-deep structures was designed to mitigate these issues. The inclusion of later arrivals in the waveform tomography resulted in a velocity model that extends to a depth of approximately 1200 m, twice the maximum depth of ray coverage in the ray-based tomography. Overall, there is a good agreement between the velocity model and a sonic log from a well on the seismic line, as well as between modeled shot gathers and field data. Anomalous zones of low velocity in the model correspond to previously identified faults or their upward continuation into the shallow Pliocene section where they are not readily identifiable in the conventional migration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".