Spatiotemporal Analysis of Seismotectonic State of Injection‐Induced Seismicity Clusters in the Western Canada Sedimentary Basin
Bibliographic record
Abstract
Abstract The observations of spatiotemporal distribution of seismicity in western Canada indicate that the occurrence of earthquakes is tied to the hydraulic fracturing operations and disposal of coproduced wastewater. In this study, we investigate the temporal changes in the frequency‐magnitude distributions for multiple clusters of induced events in regions where the level of background seismicity is low. The induced events are clustered into six major groups using density‐based spatial and soft clustering algorithms based on their epicenters. Each cluster is identified by different distributions of earthquake magnitudes and injection scenarios. The linear relationship between the number of induced earthquakes and cumulative injection volume enables us, on a regional scale, to quantitatively characterize the seismotectonic conditions of the clusters using the estimates of the seismogenic indices. The seismogenic index provides a means to estimate the occurrence probability of earthquakes with a given magnitude induced during injection. The calculated seismogenic indices agree very well with the expected seismic response to hydraulic fracturing and wastewater disposal and show a strong correlation with tectonically accumulated strain energy. Statistical models based on the seismogenic index can be employed to mitigate the potential risk of large magnitude induced events.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".