Application of moment tensor inversion for the evaluation of failure components of induced microseismicity
Bibliographic record
Abstract
The evaluation of the volumetric and shear failure components at seismic event locations is carried out using the moment tensor inversion of observed seismic displacements (e.g., Strelitz, 1978; Jost and Hermann, 1989). Applications based on mine induced seismicity offer valuable additional information for the design and planning of mining operations. The methodology mployed in these applications is based on the quasiautomatic evaluation in the time domain of the observed low frequency displacements as a combination of squared displacements and velocities with first polarities attached (Trifu et al, 2000; Trifu and Shumila, 2001, 2002). At Kidd mine (Ontario, Canada), a sill pillar at depth is investigated in connection to associated increased stress levels and the generation of microseismicity. Although critical for hauling operations at this open stop mine, the pillar appears to pose an imminent danger and the mine is evaluating its controlled destruction. However, failure analysis of the seismicity occurred within this pillar outlines a mechanism characterized by a major tensile component (72-76%), seconded by minor pure-shear (15- 20%). This typical crack opening mechanism supports the conclusion that the pillar only exhibits incipient bursting conditions, as serious deterioration would be characterized by pure-shear fractures. Instead, pureshear failures tend to locate outside this pillar, within highly fractured rock mass. The pillar was consequently maintained and continued to be used, although kept under control. For a similar mining operation at Darlot (Western Australia), the question is raised whether the microseismicity is associated with the mapped faults or the mining stops. The mechanism results outline the presence of a large pure-shear failure component (up to 60%) and a significant volumetric component (20-40%). The mine geological model permits the evaluation of the smallest divergence angle between the orientations of either of the two nodal planes of the pure-shear component and that of the closest elemental fault cell, as well as that of the average fault. The results show significant divergence angles of 30–60o. Since synthetic tests show that the mechanism solution is retrieved to within 10–15o even under up to 30% amplitude variance simulating unaccounted attenuation effects, these results support the conclusion that the microseismicity at Darlot mine is primarily influenced by local stope and mining sequence. At Ridgeway mine (New South Wales, Australia), a sublevel caving, the mechanism analysis supports the finding that the distribution of microseismicity provides a leading assessment of the caving front from the top of the loosened zone to the cave back, a zone that extends over approximately 20 m. Failure mechanisms show the presence of a high percentage of pure-shear (> 50%), together with a considerable amount of volumetric failure (~ 40%). In order to cave in, the rockmass adjacent to the cave must be essentially fractured. The large amount of shear exhibited by the above mechanisms is inagreement with the presence of a highly fractured rockmass. Additionally, the tension axes tend to align to the caving front as defined by the distribution of microseismicity. These results helped the successful tracking of the cave to surface, where it broke without incidents in early October 2002.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".