A Novel Coupled Approach to Investigate the Spatiotemporal Evolution of Fracturing-Induced Seismicity: Case Study
Bibliographic record
Abstract
Abstract The recent seismicity rate increase in Fox Creek is believed to be linked to the hydraulic fracturing operations near the region. However, the spatiotemporal evolution of hydraulic fracturing-induced seismicity is not well understood. Here, a coupled approach of geology, geomechanics, and hydrology is proposed to characterize the spatiotemporal evolution of hydraulic fracturing-induced seismicity. The seismogenic faults in the vicinity of stimulated wells are derived from the focal mechanisms of mainshock event and lineament features of induced events. In addition, the propagation of hydraulic fractures is simulated by using the PKN model, in combination with inferred fault, to characterize the possible well-fault hydrological communication. The original stress state of inferred fault is determined based on the geomechanics analysis. Based on the poroelasticity theory, the coupled flow-geomechanics simulation is finally conducted to quantitatively understand the fluid diffusion and poroelastic stress perturbation in response to hydraulic fracturing. A case study of a moment-magnitude-3.4 earthquake near Fox Creek is utilized to demonstrate the applicability of the coupled approach. It is shown that hydraulic fractures propagated along NE45° and connected with one North-south trending fault, causing the activation of fault and triggered the large magnitude event during fracturing operations. The barrier property of inferred fault under the strike-slip faulting regime constrains the nucleation position of induced seismicity within the injection layer. The combined changes of pore pressure and poroelastic stress caused the inferred fault to move towards the failure state and triggered the earthquake swarms. The associated spatiotemporal changes of Coulomb Failure Stress along the fault plane is well in line with the spatiotemporal pattern of induced seismicity in the studied case. Risks of seismic hazards could be reduced by decreasing fracturing job size during fracturing stimulations.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".