Seismic <i>b</i> value within the Montney play of northeastern British Columbia, Canada
Bibliographic record
Abstract
Critical analysis of induced earthquake occurrences requires comprehensive data sets obtained by dense seismographic networks. In this study, using such data sets, I take a detailed investigation into induced seismicity that occurred in the Montney play of northeastern British Columbia, mostly caused by hydraulic fracturing. The frequency–magnitude distribution (FMD) of earthquakes in several temporal and spatial clusters show fundamental discrepancies between seismicity in the southern Montney play (2014–2018) and the northern area (2014–2016). In both regions, FMDs follow the linear Gutenberg–Richter (G–R) relationship for magnitudes up to 3.0. While in southern Montney, within the Fort St. John graben complex, the number of earthquakes at larger magnitudes falls off rapidly below the G–R line, within the northern area with a dominant compressional regime, the number of events increases above the G–R line. This systematic difference may have important implications with regard to seismic hazard assessments from induced seismicity in the two regions, although caution in the interpretation is warranted due to local variabilities. While for most clusters within the southern Montney area, the linear or truncated G–R relationship provide reliable seismicity rates for events below magnitude 4.0, the G–R relationship underestimates the seismicity rate for magnitudes above 3.0 in northern Montney. Using a well-located data set of earthquakes in southern Montney, one can observe generally that (1) seismic productivity correlates well with the injected volume during hydraulic fracturing and (2) there is a clear depth dependence for the G–R b value; clusters with deeper median depths show lower b values than those with shallower depths.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".