A Study on the Largest Hydraulic Fracturing Induced Earthquake in Canada: Numerical Modeling and Triggering Mechanism
Bibliographic record
Abstract
ABSTRACT The Mw 4.6 earthquake that occurred on 17 August 2015 northwest of Fort St. John, British Columbia, is considered the largest hydraulic-fracturing-induced event in Canada, based on its spatiotemporal relationship with respect to nearby injection operations. There is a ∼5 day delay of this Mw 4.6 mainshock from the onset of fluid injection at the closest well pad (W1). In contrast, other two nearby injection wells (W2 and W3) have almost instantaneous seismic responses. In this study, we first take a forward numerical approach to investigate the causative mechanisms for the Mw 4.6 event. Specifically, three finite-element 3D poroelastic models of various permeability structures and presence or absence of hydraulic conduits are constructed, to calculate the coupled evolution of elastic stress and pore pressure caused by multistage fluid injections. Our simulation results suggest that pore pressure increase associated with the migration of injected fluid is required to accumulate sufficient stress perturbations to trigger this Mw 4.6 earthquake. In contrast, the elastic stress perturbation caused by rock matrix deformation alone is not the main cause. Furthermore, injection and seismicity at W1 may have altered the local stress field and brought local faults closer to failure at sites W2 and W3. This process could probably shorten the seismic response time and, thus, explain the observed simultaneous appearance of injection and induced seismicity at W2 and W3.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".