Bibliographic record
Abstract
Abstract The technique of amplitude variation with offset (AVO) allows geoscientists to extract fluid and lithology information from the analysis of prestack seismic amplitudes. Various AVO parameterizations exist, all of which involve the sum of three weighted elastic-constant terms. In present-day AVO approaches, the weighting terms involve either knowledge of the incidence angle only, or knowledge of both the incidence angle and the in situ VP/VS ratio. We have used the theory of poroelasticity to derive a generalized AVO approximation that provides the estimation of fluid, rigidity, and density parameters. We have combined two previously independent AVO formulations, thus reducing, instead of adding to, the total number of formulations. This new approach requires knowledge of a third parameter to compute the weights: the dry-rock VP/VS ratio. We have derived a new equation and applied it to model and real data sets. The new formulation has allowed us to estimate fluid properties of the reservoir in a more direct manner than previous formulations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".