Investigation of fracture zone properties using reflected seismic waves from passive microseismicity
Bibliographic record
Abstract
A new method has been developed for imaging seismic reflectors using seismogram data recorded by a few standard triaxial geophones. A directional migration approach reduces imaging artefacts due to the low aperture of the sensor array. This is possible by measuring the polarisation in the seismogram coda and considering all four reflected body-waves: PP', PS', SP' and SS'. This technique has been applied to seismograms recorded by deep borehole sensors at Williams mine, Canada, in order to invert for fracture zone properties surrounding the open pit. A fracture zone thickness of 20 m, with average rock quality designation (RQD) of 75%, best matches the seismic data, and is closely correlated to the mine's borehole core observations. This finding has useful implications for efforts to remove tunnel reflections from seismograms recorded by standard (short borehole) geophones underground. As such, it is a necessary first step before standard microseismic monitoring arrays can be used to image the rock mass beneath and ahead of a working underground mine using reflection seismology.
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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".