3-D attenuation tomography from microseismicity in a mine
Bibliographic record
Abstract
SUMMARY We perform 3-D attenuation tomography using microseismic data recorded during an underground mine development. The whole path attenuation parameter t* is obtained by least-squares inversion of P-wave amplitude spectra of the events recorded by 7 monitoring wells each containing 4 3C geophones. The corner frequencies obtained during P-wave spectral inversion of the 488 identified events range from 140 to 220 Hz which are typical for microseismic events with a negative moment magnitude of around –1. The quality factor Q obtained from tomographic inversion varies between 9 and 72 with the event cluster location characterized by a low Q value of 10. Two high Q regions of 30–72 are located at depths of 0.45 and 0.5 km, one between 0–0.15 km east and 0.3–0.5 km north which correlate with the high-grade ore deposit, and another centred around 0.45 km east and 0.25 km north. The high (-low) Q values, in general, correlates with the high (-low) velocities present in the velocity tomography model. A joint interpretation of seismic attenuation and velocity models reveals the heterogeneity present in the mine which aids in delineating the ore body using seismic waves in addition to other measurements such as gravity inversion and direct sampling from drillholes.
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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 | 0.001 | 0.001 |
| 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".