Characterisation of seismic activity at a kimberlite block caving operation in a complex geological setting in Quebec, Canada
Bibliographic record
Abstract
Stornoway Diamonds’ Renard Mine is an inclined block caving operation that began underground production of more than 6,000 tonnes per day from two kimberlite pipes in 2018. After the resumption of operations in September 2020 after a temporary shutdown due to the COVID-19 pandemic, it was observed by underground workers and the mine’s ground control department that the seismic activity rate had increased. Three large events greater than magnitude MN 2 occurred within one month during the spring of 2021. Based on underground observations, the probable source of these events was a normal fault slip in proximity to a 90,000 m3 underground void, and no major damage to active excavations was observed. A seismic system was brought online in September 2021, and it has served numerous functions to date, most important of which is to enhance the understanding the seismic hazard in the mine’s active excavations. A considerable portion of the seismic activity has taken place between the primary Renard 2 pipe (R2) and the nearby smaller secondary Renard 3 pipe (R3) located 100 m to the southeast of the R2 pipe which indicates a strong interaction between these zones. Moment tensor inversions were completed of more than 1,000 seismic events; the mine’s in situ stress orientation was estimated and used to calibrate the mine’s numerical models. The source mechanisms of the seismic events are contextualised with spatial data related to mining activities to categorise the seismicity (such as caving events and slip-type events on geological structures) and to understand the rock mass response to mining over time. The seismic system is used by the mining operation to visualise the seismicity in real time, and in collaboration with the Institute of Mine Seismology, analysis of the seismic data has allowed the operation to understand the seismic response to mining in a complex geological setting.
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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 | 0.001 | 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) | 0.001 | 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 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".