High-Resolution Imaging of Hydraulic-Fracturing-Induced Earthquake Clusters in the Dawson-Septimus Area, Northeast British Columbia, Canada
Bibliographic record
Abstract
Abstract The number of earthquakes in the western Canada sedimentary basin (WCSB) has increased drastically in the last decade related to unconventional energy production. The majority of reported earthquakes are correlated spatially and temporally with hydraulic fracturing (HF) well stimulation. In this study, we use waveform data from a new deployment of 15 broadband seismic stations in a spatial area of roughly 60×70km2, covering parts of the Montney Formation, to study the relationship between earthquakes and HF operations in the Dawson-Septimus area, British Columbia, Canada, where the two largest HF-related earthquakes in WCSB to date, an Mw 4.6 on 17 August 2015 and an ML 4.5 on 30 November 2018, have occurred. We use an automated short-term average/long-term average algorithm and the SeisComP3-software to detect and locate 5757 local earthquakes between 1 July 2017 and 30 April 2019. Using two clustering techniques and double-difference relocations of the initial catalog, we define event families that are spatially associated with specific wells, and exhibit temporal migration along a horizontal well bore and/or multiple fractures close to wells. Relocated clusters align in two dominant orientations: one roughly perpendicular to the maximum horizontal regional stress direction (SH) and several conjugate structures at low angles to SH. Comparing the two predominant seismicity lineations to regional earthquake focal mechanisms suggests that deformation occurs via thrust faulting with fault strike oriented perpendicular to SH and via strike-slip faulting with strike azimuth at low angles to SH. Local scale seismicity patterns exhibit clustering around individual HF wells, whereas regional scale patterns form lineations consistent with deformation on faults optimally oriented in the regional stress field.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".