Performance assessment of the induced seismicity traffic light protocol for northeastern British Columbia and western Alberta
Bibliographic record
Abstract
Abstract In response to the increasing concern of possible seismic risk due to injection operations during development of unconventional hydrocarbon resources, regulators in both British Columbia (BC) and Alberta (AB), Canada, have adopted varying aspects of a traffic light protocol as part of their individual oversight and risk mitigation strategies. In this study, we compare the regional seismicity pattern with the database of injection parameters to assess the performance of the individual induced seismicity traffic light protocols (IS-TLP). The red-light threshold in both BC and AB is set at local magnitude (ML) = 4, which appears to be adequate in characterizing the potential seismic risk from induced earthquakes. Since 2014, there were three red-light events each in BC and AB, all related to hydraulic fracturing. In the three AB cases and one BC case, at least one 2 ≤ ML < 4 seismic event, characterized in AB as a yellow-light event, preceded the red-light event, suggesting that an IS-TLP based on escalating magnitude probably is more applicable to AB than BC. The average rate of background seismicity seems to be positively correlated with the rate of seismicity during injection in a qualitative sense. This observation illustrates that detailed knowledge on background seismicity may be a useful reference in forecasting the overall seismic response to injections. In some cases, once the earthquake sequence was induced, events would continue even after the hydraulic fracturing was completed. Therefore, this phenomenon of delayed triggering — i.e., earthquakes occurred after the completion of injection — can be a problem for the effectiveness of the IS-TLP and should be considered carefully. The existing magnitude-based IS-TLP can sometimes cause confusion due to the uncertainty of magnitude calculation. Specific changes can be made to improve the effectiveness of IS-TLP, including incorporation of ground-motion information, standardization of magnitude calculation, and making the IS-TLP more adaptive to local hazard conditions.
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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 | 0.002 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".