SV-P extraction and imaging for far-offset vertical seismic profile data
Why this work is in the frame
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Bibliographic record
Abstract
Abstract We have analyzed vertical seismic profile (VSP) data acquired across a Marcellus Shale prospect and found that SV-P reflections could be extracted from far-offset VSP data generated by a vertical-vibrator source using time-variant receiver rotations. Optimal receiver rotation angles were determined by a dynamic steering of geophones to the time-varying approach directions of upgoing SV-P reflections. These SV-P reflections were then imaged using a VSP common-depth-point transformation based on ray tracing. Comparisons of our SV-P image with P-P and P-SV images derived from the same offset VSP data found that for deep targets, SV-P data created an image that extended farther from the receiver well than P-P and P-SV images and that spanned a wider offset range than P-P and P-SV images do. A comparison of our VSP SV-P image with a surface-based P-SV profile that traversed the VSP well demonstrated that SV-P data were equivalent to P-SV data for characterizing geology and that a VSP-derived SV-P image could be used to calibrate surface-recorded SV-P data that were generated by P-wave sources.
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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 | 0.001 |
| 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 it