Robust and High Resolution Imaging of Limited-Aperture DAS VSP
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
Distributed acoustic sensing (DAS) data recording a large amount of the subsurface information become more promising for real-time seismic monitoring. Therefore, fast and accurate imaging techniques are required to handle large datasets. Besides the issue of the computation cost, most of the migration methods, such as reverse-time migration (RTM) and Kirchhoff migration suffer from the artifacts, influencing the quality of the image, because of the limited-aperture data. Here, we perform a migration, based upon the Fresnel volume on the simulated geophone VSP and DAS VSP acquired by newly developed fibre-optic cables in Canada. We show that the Fresnel volume migration with a competitive runtime is superior and robust compared to the RTM and Kirchhoff migration. The angle-domain common-image gathers (ADCIGs) extracted from the Fresnel volume migration is more reliable and cleaner than that of the conventional Kirchhoff migration, used further for the AVO analysis and inversion.
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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) | 0.000 | 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