POLARIZATION AND VELOCITIES OF SHEAR WAVES USING HIGH RESOLUTION MULTI-COMPONENT SEISMIC REFLECTION
Bibliographic record
Abstract
The post-glacial marine deposits in Eastern Canada provide an ideal environment for observing body wave reflection data. Due to high stratigraphic coherence of the mud, both compressional and shear waves polarized in multiple directions can be recorded with 3-C geophones mounted on a land streamer with minimal interference from surface waves or ground roll. Based on our observations, the polarization of P-wave reflections is almost always vertical. In comparison, most of the observed shear wave reflections are in the horizontal plane when the near surface shear velocity is ∼300 m/s or higher. However, as near surface velocities become less than 300 m/s, the waves can be polarized in multiple directions depending on the site conditions. The polarization can vary from vertical to horizontal as a function of arrival time. We find that the processing of S-wave data requires great accuracy in the determination of stacking velocities. To ensure quality of the S-wave sections, the velocity must be determined using semblance velocity analysis within an error range of less than 5 m/s in areas where very high-frequency shallow shear wave reflections are observed. Using a multi-component portable vibrator such as our in-house development called “Microvibe,” we demonstrate that the vertical stacking velocity can be significantly lower for the shear waves in vertical propagation mode than for those in the horizontal transverse mode, thus leading to the observation of a birefringence effect between the vertical and the horizontal planes. Our experience with shear wave reflection profiling over the past 5 years has convinced us of the great potential of this technique. Shear waves offer another way to image the subsurface that provides extraordinary resolution in some circumstances, and can yield results where more traditional compressional wave methods fail. We are learning that with careful data collection, we can observe the true complexity of the propagation of seismic energy in the near surface. Some of these complexities such as polarization changes and velocity anisotropy provide us with new insights and new ways to measure the physical properties of the near-surface.
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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".