Experimental study of seismic anisotropy in artificial clay-rich shales
Bibliographic record
Abstract
Clays are among the main mineral components of shales in the USA, Canada and China and play important roles in velocity anisotropy. Unlike brittle minerals, e.g., quartz, ductile clays are commonly more easily affected by mechanical compaction. Hence, clays tend to have a platy structure that might introduce significant velocity anisotropy. Cracks developed in clay-rich shales also have substantial influences on the shale elastic anisotropy and hydraulic stimulation. In this study, we construct artificial clay-rich shales which contain 40% clays by weight (kaolinite, smectite, and illite, respectively). P-wave and S-wave velocities are measured as the axis pressure (Pa) increases from 15 MPa to 50 MPa, while the confining pressure (Pc) remains at 15 MPa. We estimate the crack density using an NIA model, and calculate the theoretical validation based on the parameters of laboratory data. We analyze the velocity anisotropy effect from clays and cracks based on laboratory experiments and theoretical validation.
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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 | 0.000 | 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 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".