Bibliographic record
Abstract
Abstract The seismic reflection characterizations of a thin layer are important for reservoir geophysics. However, discussions on the reflection for a thin layer are usually restricted to precritical angle incidence. In this work, an exact analytical solution is derived to model the reflection amplitude and amplitude variation with offset (AVO) responses of a single thin bed for arbitrary incident angles. The results show that the influence of an ultra-thin bed is great for opposite-polarity reflections and is small for identical-polarity reflections. Opposite-polarity precritical reflection amplitudes first decrease in magnitude with the wavelength/thickness ratio to a local minimum, then increase to a maximum, and finally decrease gradually to zero as the layer vanishes. Opposite-polarity postcritical reflections monotonically decrease from near unity to zero, proportional to the thickness of the layer. Identical-polarity precritical reflection amplitudes first increase in magnitude with the wavelength/thickness ratio to a local maximum, then decrease to a minimum, and finally increase to the amplitude of a single bottom reflection when the layer vanishes. Identical-polarity postcritical reflections have magnitudes near unity. The AVO responses for both opposite and identical-polarity acoustic thin beds gradually increase with angle. The influence of the Poisson's ratio of the thin bed is small for either small incidence angles or thicknesses less than 7% of the seismic wavelength, but is large for high incidence angles or thicknesses greater than 13% of the wavelength. A decrease of Poisson's ratio causes a pronounced AVO response that reaches its maximum at the quarter-wavelength tuning thickness.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
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 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".