Basin-scale multi-decadal analysis of hydraulic fracturing and seismicity in western Canada shows non-recurrence of induced runaway fault rupture
Bibliographic record
Abstract
Abstract Hydraulic fracturing (HF) is a reservoir stimulation technique that has been widely deployed in recent years to increase the productivity of light oil and/or natural gas from organic-rich, low-permeability formations. Although the process of fracturing a rock typically results in microseismic events of magnitude < 0, many cases of felt seismic events (typically magnitude 3.0 or larger) have also been reported. In the Western Canada Sedimentary Basin (WCSB), where more than 40,000 wells have been drilled and hydraulically fractured in the past two decades, the occurrence of HF-induced events has surged in some areas. Yet, many other areas of the WCSB have not experienced a significant increase in induced seismicity, despite a sharp increase in both the number of HF wells and the volumes of injected fluid. The relationship between injected volume and induced magnitudes can be quantified using the seismic efficiency ratio (S EFF ), which describes the ratio between the net seismic moment release and the injected fluid volume. Runaway rupture, in which the fault rupture is dominated by the release of accumulated tectonic stresses, is inferred to be marked by an abrupt increase in S EFF to a value > 0.5. Most previous studies of induced earthquakes have been limited to a single operation and/or seismicity sequence. To better understand the observed variability of the seismic response to HF stimulations at a basin scale, we compiled HF data for all unconventional wells hydraulic fractured in the WCSB between 2000 and 2020, together with the seismicity reported during the same period. We grouped these observations into bins measuring 0.2° in longitude and 0.1° in latitude, or approximately 13 by 11 km. We identified 14 areas where large magnitude events resulted in high S EFF values, implying runaway rupture had taken place. However, we find that in these areas, sustained fluid injection did not lead to persistent high S EFF values. Instead, as injection continued, S EFF values returned to values less than 0.5. This suggests that there is a limited budget of tectonic strain energy available to generate runaway rupture events: once this is released, event magnitudes decrease even if high volume injection persists.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| 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".