Spatiotemporal Variations in Earthquake Triggering Mechanisms During Multistage Hydraulic Fracturing in Western Canada
Bibliographic record
Abstract
Abstract Dense arrays deployed near the hydraulic fracturing (HF) wells greatly enhance the understanding of injection‐induced seismicity. In this study, we revisit the continuous recordings that are acquired by 69 three‐component nodes at an HF site in Alberta, Canada, taking advantage of a machine learning‐based seismic detection and location workflow. The obtained new earthquake catalog contains 21,619 events with relative location errors of <1 m, which exceeds ∼20% of the number of earthquakes (18,040) reported previously (Igonin et al., 2021). This high‐resolution catalog reveals the distribution of earthquake sequences at much improved spatiotemporal resolution and illustrates several previously unmapped faults/fractures. Earthquake frequency‐magnitude distribution reveals that the average b value increases with depth from ∼1.1 above 3.5 km to ∼2.5 at greater depths. Further spatial analysis of seismic clusters indicates that the b value varies laterally (∼1–1.7) at shallow depths and is inversely related to the proximity to injection wells in conjunction with the change in structural types (i.e., reactivated fault and pre‐existing fracture). The seismic sequence on the north‐south oriented faults also shows a distinctive occurrence pattern and temporal affinity to the fracturing network reactivation between the two stages of HF operations. The change in faulting behavior could reflect a shift of dominating triggering mechanisms and physical processes from (a) the rapid diffusion of pore fluid pressure along pre‐existing fracture corridors to (b) the cascade migration of earthquake sequences in response to the cumulative Coulomb stress perturbation on the fluid‐lubricated, critically stressed faults.
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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 | 0.002 | 0.000 |
| 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 | 0.002 |
| 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".