Optimum source-receiver orientations to capture PP, PS, SP, and SS reflected wave modes
Bibliographic record
Abstract
Abstract We conducted a field experiment at the geotechnical research soil site #1 in Ottawa, Ontario, Canada, and recorded 9-C seismic data along a short line traverse 90 m in length using a multicomponent vibrator source named Microvibe and a landstreamer receiver array with 48 3-C 28-Hz geophones at 0.75-m intervals. The receiver spread length is 35.25 m, and the near-offset is 1.50 m. We used three source and three receiver orientations — vertical (V), inline-horizontal (H1), and transverse-horizontal (H2). We identified several reflection wave modes in the field records — PP, PS, SP, and SS, in addition to refracted waves, and Rayleigh-mode and Love-mode surface waves. We computed the semblance spectra of the selected shot records and ascertained the wave modes based on the semblance peaks. We then performed CMP stacking of each of the 9-C data sets using the PP, PS/SP, and SS stacking velocities. This field test convincingly demonstrates that there is no pure P- or S-wave land seismic source — any source type can generate any combination of wave modes — PP, PS, SP, and SS, and partitioning of the source energy depends on the source orientation and VP/VS ratio. All three receiver orientations will capture all reflected wave modes — PP, PS, SP, and SS — but with varying strength. The magnitude of the reflection amplitude captured by one of the three receiver orientations will depend on the reflector depth, source-receiver offset, and the near-surface P- and S-wave velocities in the vicinity of the receiver location. The most prominent PP reflection energy is recorded by the VV source-receiver orientation, whereas the most prominent SS reflection energy is recorded by the H2H2 source-receiver orientation. Additionally, the optimum source-receiver orientation for PS reflection mode is VH1, and the optimum source-receiver orientation for SP reflection mode is H1V.
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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) | 0.001 | 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 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".