Reprocessing and Characterization of Long-duration Tremor Signals from a Hydraulic-fracture Treatment in Western Canada
Bibliographic record
Abstract
Summary The Hoadley flowback microseismic experiment (HFME) was undertaken commencing August 2012 for long-term passive seismic monitoring in a open-hole multistage hydraulic fracture treatment in the Glauconitic member (Hoadley gas field, central Alberta). The scientific goals of this project were to document and develop a geomechanical model for microseismic activity associated with flowback and production stages of development of a tight-gas reservoir. About 1650 events were located during the two-day hydraulic fracture treatment program. The distribution of microseismicity revealed a relatively complex fracture pattern. The objectives of this study are twofold. First, complete reprocessing of the raw microseismic data has been undertaken using in-house software, with the goal of improving the understanding of the relationship between source type (shear versus tensile) and the treatment parameters. The second goal is to characterize long-duration tremor-like events that occurred episodically during and after treatment. These events are interpreted as activation of slow slip on pre-existing fractures. Two of these tremor-like events occurred during the postpumping period after the second day of treatment; they both exhibit frequency characteristics that are consistent with a slowly cascading rupture process.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".