Seismogenic Potential of Hydraulic Fracturing in the South Montney Play, Northeast British Columbia: A Seismogenic Index Approach
Bibliographic record
Abstract
Abstract Understanding the seismogenic potential of fluid injection, such as hydraulic fracturing (HF), is essential for the assessment of seismic hazards of unconventional reservoirs. This study integrates statistical and seismotectonic analyses to characterize induced seismicity and quantify its potential impact associated with the South Montney Play. A comprehensive earthquake catalog, combined with detailed HF operation records, is analyzed using density-based spatial clustering and frequency–magnitude distributions. The results indicate that seismicity is predominantly associated with HF targeting the Lower-Middle Montney (LMM) formation, which accounts for more than 90% of the induced events. The classic Gutenberg–Richter relation and the lower-bound approach were employed to analyze the spatial variations of the b-value, revealing significant variability ranging from approximately 0.5 to 2.5. The lowest b-values, concentrated in LMM-associated clusters, suggest an elevated probability of larger-magnitude events. A significant negative correlation is observed between b-values and the maximum magnitudes of induced earthquake clusters, reinforcing the importance of b-value in hazard forecasting. The seismogenic index further quantifies the susceptibility of different clusters to induced seismicity, providing a statistical basis for earthquake forecasting models. The strong agreement between observed and forecasted seismicity validates the applicability of statistical models derived from seismogenic index to assess the seismic hazard induced by HF. These findings establish a robust framework for seismic risk mitigation, emphasizing the importance of statistical seismology in improving hazard forecasting and regulatory decision-making in unconventional resource development.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".