A comprehensive earthquake catalogue for northeastern British Columbia: the northern Montney trend from 2017 to 2020 and the Kiskatinaw Seismic Monitoring and Mitigation Area from 2019 to 2020
Bibliographic record
Abstract
To increase our understanding of induced seismicity, we develop and implement methods to enhance seismic monitoring capabilities in northeastern British Columbia (NE BC). We deploy two different machine learning models to identify earthquake phases using waveform data from regional seismic stations and utilize an earthquake database management system to streamline the construction and maintenance of an up-to-date earthquake catalogue. The completion of this study allows for a comprehensive catalogue in NE BC from 2014 to 2020 by building upon our previous 2014-2016 and 2017-2018 catalogues. The bounds of the area where earthquakes were located were between 55.5°N-60.0°N and 119.8°W-123.5°W. The earthquakes in the catalogue were initially detected by machine learning models, then reviewed by an analyst to confirm correct identification, and finally located using the Non-Linear Location (NonLinLoc) algorithm. Two distinct sub-areas within the bounds consider different periods to supplement what was not covered in previously published reports - the Northern Montney Trend (NMT) is covered from 2017 to 2020 while the Kiskatinaw Seismic Monitoring and Mitigation Area (KSMMA) is covered from 2019 to 2020. The two sub-areas are distinguished by the BC Oil & Gas Commission (BCOGC) due to differences in their geographic location and geology. The catalogue was produced by picking arrival phases on continuous seismic waveforms from 51 stations operated by various organizations in the region. A total of 17,908 events passed our quality control criteria and are included in the final catalogue. Comparably, the routine Canadian National Seismograph Network (CNSN) catalogue reports 207 seismic events - all events in the CNSN catalogue are present in our catalogue. Our catalogue benefits from the use of enhanced station coverage and improved methodology. The total number of events in our catalogue in 2017, 2018, 2019, and 2020 were 62, 47, 9579 and 8220, respectively. The first two years correspond to seismicity in the NMT where poor station coverage makes it difficult to detect small magnitude events. The magnitude of completeness within the KSMMA (ML = ~0.7) is significantly smaller than that obtained for the NMT (ML = ~1.4). The new catalogue is released with separate files for origins, arrivals, and magnitudes which can be joined using the unique ID assigned to each event.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".