Methane Emissions from Non-producing Oil and Gas Wells and the Potential Role of Seismic Activity: A Case Study in Northeast British Columbia, Canada
Bibliographic record
Abstract
Increasing seismic activity due to fluid injections for oil and gas production may be contributing to leakage along non-producing oil and gas wells and emitting methane, a potent greenhouse gas. However, the extent to which nearby seismicity may drive or exacerbate methane emissions and cause well integrity issues is unknown. Therefore, we analyze field evaluations at 448 non-producing oil and gas wells in Northeast British Columbia (NEBC) and geospatially analyze oil and gas well and fluid injection data alongside locations of 3515 earthquakes from 2001 to 2021 and 130 faults. Through analysis of ground and helicopter-based field evaluations of non-producing wells in NEBC, we show that methane emission rates of non-producing wells average at 8301 mg/h/well but vary by 10 orders of magnitude. We find that higher methane emission rates (milligrams of methane/h/well) are observed at wells with larger flowing pressures at the wellhead during completion (kPa) and with shorter distances (m) to earthquakes, particularly at plugged wells. These results imply that seismicity may increase the likelihood of non-producing well integrity issues and methane leakage, thereby also exacerbating groundwater contamination and environmental degradation risks.
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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 | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 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".