Computing Near-surface S-wave Velocity Models by Inversion of Converted-wave Traveltime Differences
Bibliographic record
Abstract
Summary Characterizing the near-surface is an important part of solving seismic static problems. It is also a critical step as input for more general iterative inversion methods applied to land seismic data. In the case of converted waves this becomes even more true due to the large magnitudes of the shear-wave statics. In this study, a solution based on the difference in conversion traveltimes between receivers is proposed. This solution may be useful for inverting delay times retrieved by interferometric techniques. Due to the complexity of the partial derivatives of the forward modelling operator for this case we decided against local descent-based methods, adopting instead a simulated annealing inversion method. This is also justified by the complex topography of the objective function. Performing a representative number of iterations of the proposed algorithm successfully retrieves the true parameters of the model. Since traveltime differences were used, the inverted parameters only allowed us to compute changes in the depth of the base of the near-surface rather than its absolute value. This can be fixed through a calibration process given the depth of the low velocity zone for at least at one receiver location.
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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".