Converted-wave seismic exploration: Methods
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Multicomponent seismic recording (measurement with vertical- and horizontal-component geophones and possibly a hydrophone or microphone) captures the seismic wavefield more completely than conventional single-element techniques. In the last several years, multicomponent surveying has developed rapidly, allowing creation of converted-wave or P-S images. These make use of downgoing P-waves that convert on reflection at their deepest point of penetration to upcoming S-waves. Survey design for acquiring P-S data is similar to that for P-waves, but must take into account subsurface VP/VS values and the asymmetric P-S ray path. P-S surveys use conventional sources, but require several times more recording channels per receiving location. Some special processes for P-S analysis include anisotropic rotations, S-wave receiver statics, asymmetric and anisotropic binning, nonhyperbolic velocity analysis and NMO correction, P-S to P-P time transformation, P-S dip moveout, prestack migration with two velocities and wavefields, and stacking velocity and reflectivity inversion for S-wave velocities. Current P-S sections are approaching (and in some cases exceeding) the quality of conventional P-P seismic data. Interpretation of P-S sections uses full elastic ray tracing, synthetic seismograms, correlation with P-wave sections, and depth migration. Development of the P-S method has taken about 20 years, but has now become commercially viable.
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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) | 0.003 | 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 it