Integration of 3C Borehole and 3D Surface Seismic Data
Bibliographic record
Abstract
In exploration seismology, imaging requires comprehensive information so as to obtain a qualitative evaluation of an area of interest. In the presence of an existing borehole in a given survey area, a way this can be achieved is by conducting an integrated study using 3D surface seismic data with a 3C borehole sensor fixed at depth to simultaneously record the surface shots. Valuable information like travel time, velocities, amplitude variations ( with offset and azimuth), and attenuation can be extracted from the borehole sensor to help complement the processing and interpretation of the 3D reflection data. 3C-borehole data, acquired as part of a 3D seismic survey, from the Sudbury Structure was analyzed to evaluate its potential use. Polarization analysis showed its value as a quality control tool in checking the directions of the surface shots. First break travel time analysis also suggested azimuthal velocity variations in the surveyed zone. Such information is important for obtaining a 3D macrovelocity structure and as input for migration of the 3D data set. In addition, estimates of shot statics were obtained from the borehole data.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".