How did hydraulic-fracturing operations in the Horn River Basin change seismicity patterns in northeastern British Columbia, Canada?
Bibliographic record
Abstract
Abstract An increase in regional seismicity has been documented for the Horn River Basin (HRB) since the development of shale gas began in late 2006. Operational parameters of all hydraulic-fracturing (HF) treatments in the HRB between November 2006 and December 2011 were compiled from completion reports collected by the British Columbia Oil and Gas Commission (BCOGC). This database was compared with regional earthquake catalogs to delineate a quantitative relationship between the observed variation of regional seismicity and local HF operations. Taking the HRB as a whole, results suggest that the total injected volume from hydraulic fracturing is a more significant factor in affecting the pattern of local seismicity than injection pressure is. However, no clear change in background seismicity can be observed when the total monthly injected volume is less than ∼ 20,000 m3. The initial effect of increasing injected volume is an increase in earthquake frequency but not magnitude. Relatively large seismic- moment release (> 1014 N m) occurred only when the monthly injected volume exceeded ∼ 150,000 m3. Variable time lags, from days to four months, are observed between intense HF and the occurrence of a significant local earthquake. The hydrologic properties of the source formations and local geologic conditions (such as distribution, geometry, and dimension of preexisting faults) also might play important roles in induced seismogenesis, in addition to the total volume of injection.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".