Passive Seismic Imaging of Stress Evolution with Mining-Induced Seismicity at Hard-Rock Deep Mines
Bibliographic record
Abstract
Abstract This work aims to examine the stress redistribution with evolving seismicity rates using a passive seismic tomographic tool. We compiled a total of 26,000 events from two underground mines and partitioned them into multiple clusters in a temporal sequence, each of which contains 1000 events. To image stress redistribution associated with seismicity rates, we then run the tomographic studies using each cluster to yield seismic tomograms and computed the corresponding seismicity rate. We found that high velocity anomalies grew with the increase of seismicity rates, and they switched to a shrinking tendency under low seismicity rates. Results of this study imply that seismicity rates increase with increasing stress concentration and decrease with decreasing stress concentration. This study highlights the value of utilizing passive seismic tomography for estimating stress evolution associated with the change of seismicity rates at underground mines. Our findings illuminate the applications of using mining-induced seismicity to assess stress redistribution associated with seismicity rates at hard-rock mines, providing insights into seismic hazards for deep mining.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".