Seismic response of large-scale to medium-scale geological structures in deep mines
Bibliographic record
Abstract
Successful mining projects rely on three interconnected pillars: maintaining a safe working environment, achieving uninterrupted production at the required mining rate and ore grade, and managing costs effectively. A strong seismic response either during mine development or stope extraction constitutes a potential safety hazard and it can eventually affect the delivery of the mine plan. The anticipated rock mass behaviour around mine excavations depends on the effect of the in situ stress field on local rock mass conditions. Both are directly related to the geological and tectonic history of the deposit and regional environment. The geometry, strength and stiffness of large-scale structural features such as brittle faults, ductile shear zones and dykes have a direct and significant impact on the surrounding rock masses and local stress field. The Goldex and LaRonde mines in Canada, and the Kittilä mine in Finland, are deep underground seismically active mines in different geological settings. The seismic responses of medium to large-scale geological structures and dykes encountered at Goldex and select examples from LaRonde and Kittilä mines illustrate some of the lessons and ongoing work to assist in managing the seismic risk at these operations. The seismic response of large to medium-scale structures is challenging to anticipate and manage until actual mining has taken place and monitoring data is available. For instance, the seismic response associated with graphitic shears and jointing in the footwall at Rimpi, the milder-than-expected response of the diabase dykes and the stronger than expected response of the mylonitic ductile shears and brittle faults at Goldex were unforeseen. Even in a mature mine such as LaRonde, the understanding of the behaviour of the 700 Fault has taken some time to develop. The examples provided in this paper aim to demonstrate the benefits of integrating structural geology and improving the characterisation and modelling of the large to medium-scale structures from the earliest stages of a project. In mature mining camps, leveraging the geological and deformation history from regional geology and tectonic setting can help to anticipate potential alteration patterns and large-scale structural orientations and dykes. These structures should be included in early analyses and numerical modelling to guide the placement of mine infrastructure, strategic mine layout and mining sequence decisions.
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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".