Seismic Detection of Cracks in Carbonates Associated with Potash Mining
Bibliographic record
Abstract
Summary Brine inflow in a mine, resulting from cracks or fractures in overlying strata, can be a significant problem. This paper investigates whether cracked or fractured rock, associated with potash mining in western Canada, might be detectable by multi-component seismic methods. Rock physics modeling was carried out to simulate cracked rocks overlying a potash ore zone. The Kuster-Toksoz procedure modeled randomly distributed cracks while Hudson’s formulation was used for aligned cracks in a carbonate interval (the Dawson Bay including the Second Red Bed Shale) overlying the Prairie Evaporites. We find that cracked rocks can display a significant velocity decrease for both P- and S-velocities. For aligned cracks, velocity anisotropy was also observed. Synthetic seismograms for these cracked media show some character change (time shifts, amplitude variation with offset) compared with uncracked responses. The results provide promise for the detection of cracked rock using multi-component seismic data and repeated surveys.
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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".