The Influence of a Transitional Stress Regime on the Source Characteristics of Induced Seismicity and Fault Activation: Evidence from the 30 November 2018 Fort St. John ML 4.5 Induced Earthquake Sequence
Bibliographic record
Abstract
ABSTRACT On 30 November 2018, a sequence of seismicity including a felt (ML∼4.5) induced earthquake occurred ∼16 km southwest of Fort St. John, British Columbia. Using a local seismograph network around the epicentral region, we identified > 560 seismic events over a two-week period, incorporating two mainshock events within a 45 min time interval, both with ML>4.3. This seismicity occurred close in location and depth to ongoing hydraulic fracturing operations. Using previously unpublished data, our analysis suggests that events, including the largest mainshock, occurred at the interval of fluid injection, which is shallower than previously reported. The events showed a mix of reverse, oblique normal, and strike-slip mechanisms within a well-defined structural corridor that forms the southern margin of the Fort St. John graben. The two mainshock events reveal opposing mechanisms: one as a reverse (re)activation of a normal fault (ML 4.5) and the other an oblique normal mechanism (ML 4.3). Stress inversion and bootstrap analysis of 72 well-constrained focal mechanisms indicate that the maximum principal stress direction is horizontal, oriented in a north-northeast direction (3°–36°). However, the intermediate and minimum stress axes fluctuate between horizontal and vertical and are nearly equal in magnitude, indicating that both reverse and strike-slip regimes can occur in response to relatively small stress perturbations. Stress inversions using event subsets before and after the largest mainshock reveals an approximately 30° counter-clockwise coseismic rotation of the principal stress axes in the hypocentral region. Furthermore, the observed seismicity suggests that the largest mainshock event exceeded the calculated Mmax using models based on injected volumes, suggesting that it may be an example of runaway rupture. This has important implications for risk analysis, because small changes in the stress field may be induced through ongoing operations in this area, destabilizing different faults within a complex structural environment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".