MULTI-COMPONENT VIBRO-SEISMIC TECHNIQUES FOR ASSESSING GAS ESCAPE FEATURES, FAULTS AND LANDSLIDES
Bibliographic record
Abstract
Three-component seismic recording using landstreamers and vibrating sources is a highly efficient means of collecting seismic reflection data with the capacity of producing P-wave and S-wave profiles from the same data set. P-waves are typically vertically polarized; conversely, we usually observe that S-waves can be polarized in any direction depending on the offset and the depth of the reflectors as well as the type of ground materials. The signal quality depends strongly on the type of source used for the acquisition. Our observations show that the 3.5t Minivib™ does not provide cleanly polarized signals, although it allows fast acquisition as a significant amount of both P-wave and S-wave energy is produced even when the source is vibrating in the horizontal mode. We also have observed that the highest frequency signals are produced when the Minivib vibrates in the horizontal inline direction, but the frequency range only reaches ~250 Hz. In contrast, the latest version of our in-house 230 kg, 3-C Microvibe produces well-polarized signals with frequencies up to 800 Hz and allows acquisition of 9-C data in a single pass. We present examples of seismic profiles over groundwater and gas escape features, active faults and landslides using multicomponent, high resolution seismic data acquired in eastern Canada. Sensitive glaciomarine sediments affected by large-scale mass movements display very complex polarizations that require phase rotation processing tools. Very short, less than 1 m wavelengths observed during our shear wave data system experiments allowed us to accurately image post glacial active faults.
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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".