Seismic signatures of two orthogonal sets of vertical microcorrugated fractures
Bibliographic record
Abstract
Conventional fracture-characterization techniques operate with the idealized model of penny-shaped (rotationally invariant) cracks and ignore the roughness (microcorrugation) of fracture surfaces. Here, we develop analytic solutions based on the linear-slip theory to examine wave propagation through an effective triclinic medium that contains two microcorrugated, vertical, orthogonal fracture sets in isotropic background rock. The corrugation of fracture surfaces makes the shear-wave splitting coefficient at vertical incidence sensitive to fluid saturation, especially for tight, low-porosity formations. Also, in contrast to the model with two orthogonal sets of penny-shaped cracks, the NMO (normal-moveout) ellipses of all three reflection modes (P, S1, S2) are rotated with respect to the fracture strike directions. Another unusual property of the fast shear wave S1 is the misalignment of the semi-major axis of its NMO ellipse and the polarization vector at vertical incidence. Our model may adequately describe the orthogonal fracture sets at Weyburn Field in Canada, where the axes of the P-wave NMO ellipse deviate from the S1-wave polarization direction. The results of this work can be used to identify the underlying physical model and, potentially, estimate the combinations of fracture parameters constrained by multiazimuth, multicomponent seismic data.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".