Intensity of Induced Earthquakes in Northeast British Columbia, Canada
Bibliographic record
Abstract
Abstract The damage potential of induced earthquakes associated with fluid injection is a major concern in hydrocarbon resource development. An important source of data for the assessment of damage is macroseismic intensity perceived by people and structures. In the Western Canada Sedimentary Basin (WCSB) where the occurrence of seismicity is mostly related to oil and gas activities, the collection of intensity data is incomplete. In this study, we present a comprehensive dataset gathered by the BC Oil and Gas Commission in the period 2016–2020. We assign intensities to individual felt reports according to the modified Mercalli intensity (MMI) scale and associate each MMI value to an earthquake. The isoseismal map of the largest earthquake in the Septimus region of northeast British Columbia is also provided using the compiled intensity dataset complemented with data from the U.S. Geological Survey and Natural Resources Canada “Did You Feel It?” systems along with the intensities converted from ground-motion amplitudes. We consider an approximate 10 km radius around the mainshock of 30 November 2018 earthquake with moment magnitude of 4.6 to be the meizoseismal area based on maximum intensities of 4–5. We also investigate the distance decay of intensity for shallow induced earthquakes in comparison with deeper natural events with the same magnitudes. Although intensities from shallow earthquakes (depth≤5 km) can be higher than deep events (depth≥10 km) at close distances (10–15 km), they tend to decrease abruptly at greater distances to become lower than deep events. The localization of large intensities from induced earthquakes within the meizoseismal area warrants special attention in future resource developments and call for systematic intensity data collection in the WCSB.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".