Spatiotemporal changes in seismic velocity associated with hydraulic fracturing-induced earthquakes near Fox Creek, Alberta, Canada
Bibliographic record
Abstract
To characterize the subsurface geomechanical response to hydraulic fracturing activities, we study the spatiotemporal changes of seismic velocity during the completion of four injection wells in the Fox Creek area, Alberta, Canada. We estimate temporal velocity changes (dv/v) from ambient seismic noise recorded during the Tony Creek Dual Microseismic Experiment (ToC2ME) by comparing a 5-day stacked noise correlation function with a reference noise correlation function stacked over the deployment period. In the frequency band (0.1 - 0.4 Hz) most sensitive to the injection depths (~3.4 km), we observe daily dv/v that revealed alternating gradual velocity decreases and increases with magnitudes in the range of ±0.9%. We found a strong temporal correlation between the onset of velocity decreases and periods of intense seismicity, suggesting that the observed dv/v reductions are likely caused by stress-induced subsurface deformation due to elevated pore pressures, increased crack density, and ground shaking. A period of dv/v increase observed between the beginning and end of different well stimulation is attributed to crustal healing. Comparing the dv/v time series with injection parameters, we observed a 272.66% increase in induced seismicity and 50% more reduction in dv/v during the second injection phase that are correlated with 90.53%, 169.64%, and 4.34% increase in the injection volume, rate, and pressure, respectively. Our study provides valuable new information on the changes in reservoir elastic properties within the Western Canadian Sedimentary Basin. It also demonstrates that coda wave interferometry using data from dense seismic arrays near injection sites can be an additional tool for monitoring hydraulic fracturing operations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".