Mitigating risks from hydraulic fracturing-induced seismicity in unconventional reservoirs: case study
Bibliographic record
Abstract
The recent remarkable increase in induced seismicity in Western Canada has been largely attributed to hydraulic fracturing in unconventional reservoirs. The nucleation of large magnitude events has been demonstrated to be closely linked to site-specific geological and operational factors. A mitigation strategy of fracturing-induced seismicity concerning both factors has not been well investigated. In this paper, a comprehensive investigation of risk mitigations from induced seismicity is conducted based on the formation overpressure, distance to Precambrian basement, proximity to faults, fracturing job size and safe hydraulic fracture-fault distance. It is found that the middle-south region near Crooked Lake is an optimal region for fracturing operations with low formation pressure, a great distance to the basement and relatively fewer pre-existing faults. A field case study suggests that fracturing operations of three new horizontal wells are successful with low magnitude induced events and with high production performance, demonstrating the applicability of a comprehensive approach of seismicity risk mitigations. Such an approach can be applied to other field cases to mitigate the potential fracturing-induced seismicity in unconventional reservoirs.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".