Modelling of fluid pressure migration in a pressure sensitive fault zone subject to cyclic injection and implications for injection-induced seismicity
Bibliographic record
Abstract
SUMMARY Fault zones often serve as the major fluid pathways in a variety of geo-energy systems, such as deep geothermal systems. However, injection-induced instability of faults can sometimes lead to large-magnitude earthquakes. Cyclic injection has thus been proposed as an alternative injection protocol to better manage and mitigate the associated seismic risks. The risks of injection-induced seismicity depend primarily on the extent and magnitude of the fluid pressure perturbation. When fluid is injected into a fault zone, the local fault permeability will be enhanced, which in turn promotes the migration of fluid along the fault. This nonlinear process is further complicated during cyclic injection via alternating the injection pressure. In this study, both numerical and analytical modelling are conducted to investigate cyclic fluid injection into a fault zone with pressure sensitive permeability, in which the local fault permeability changes as a function of the local effective stress. The match with laboratory-scale experimental and field-scale analytical results of cyclic fluid injection verifies the accuracy of the numerical model. The parametric study reveals that the injection pressure attenuation, quantified by the amplitude ratio and phase shift, is enhanced by a lower initial fault permeability, a smaller stress sensitivity coefficient and a shorter period of pressure cycle (i.e. a higher frequency). Besides, the amplitude of the pressure cycle has a negligible effect on the injection pressure attenuation. We also discuss the implications of our results for the less amenable far-field seismic hazard and post shut-in seismicity.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".