Characterizing hydraulic fracture behaviour in the Horn River Basin with microseismic data
Bibliographic record
Abstract
Focal mechanisms from microseismic events contain an abundance of information. Moment tensor inversion can lead to a richer understanding of the failure mechanisms and stresses at work at the event source. This information cannot be ascertained from event hypocenter locations alone. Often events recorded during hydraulic fracturing are associated with double-couple (DC) source mechanisms. Hydraulic injection has been associated with non-shear source mechanisms, hence constraining the source mechanism to a shear solution is not appropriate. Data from passive surface monitoring in the Horn River Basin are used to explore moment tensor decompositions. We show that events relating to hydraulic fractures contain significant compensated linear vector dipole (CLVD) components of failure and exhibit b-values of approximately 2. This event population is in contrast to fault reactivation events, which are highly double-couple and have a b-value of approximately 1. This work is part of an ongoing study to integrate geophysical, geological and engineering information.
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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 | 0.002 | 0.002 |
| 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".