Analysis of the Hydrogeological Conditions Affecting Fault Response to Nearby Hydraulic Fracturing
Bibliographic record
Abstract
Abstract The response of critically stressed dormant faults to fluid perturbation, by oil and gas production, has been a major public concern because of its link to induced seismicity. In this paper, we study the hydrogeological factors that affect a nearby fault response, during and after hydraulic fracturing (HF) operations, evaluated by the change in Coulomb Failure Stress (CFS) and the rate of seismicity ( R ) through coupling solid deformation and fluid flow. Our results show that the pore pressure increases rapidly in a fault that is close (hydraulically connected) to HF operations, which might lead to its activation when the injection rate is high. When the fault is adjacent to HF but distant from it, its shallow region is subjected to a stabilizing deformation‐induced normal compressive stress and its deeper region is destabilized under extension. In this case, the fault orientation and damage zone size have a significant effect on the fault's stability and response. On the other hand, decreasing the rate of injection can either increase or decrease the CFS values depending on the fault location and the dominant stresses. Therefore, serious attention should be given to the fault position, its architecture, and the injection rate to help reduce the potential for induced seismicity from HF. Our findings are verified and confirmed using the case of the Duvernay formation in Alberta, Canada, where the reported seismic data correlate with high CFS and R values.
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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 | 0.001 |
| 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) | 0.001 | 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".