Advancing knowledge of gas migration and fugitive gas from energy wells in northeast British Columbia, Canada
Bibliographic record
Abstract
Abstract Petroleum resource development is creating a global legacy of active and inactive onshore energy wells. Unfortunately, a portion of these wells will exhibit gas migration (GM), releasing fugitive gas (FG) into adjacent geologic formations and overlying soils. Once mobilized, FG may traverse the critical zone, impact groundwater, and emit to the atmosphere, contributing to greenhouse‐gas emissions. Understanding of GM and FG has increased in recent years but significant gaps persist in knowledge of (1) the incidence and causes of GM, (2) subsurface baseline conditions in regions of development required to delineate GM and FG, and (3) the migration, impacts, and fate of FG. Here we provide an overview of these knowledge gaps as well as the occurrence of GM and FG as currently understood in British Columbia (BC), Canada, a petroleum‐producing region hosting significant reserves. To address the identified knowledge gaps within BC, the Energy and Environment Research Initiative (EERI) at the University of British Columbia is implementing several field‐focused research projects including: (1) statistical analyses of regulatory data to elucidate the incidence and causes of GM, (2) characterization of regional hydrogeology and shallow subsurface conditions in the Peace Region of the Montney resource play, and (3) investigation of the migration, impacts, and fate of FG in the shallow subsurface through controlled natural‐gas release. Together, the EERI investigations will advance understanding of GM and FG, provide scientific data that can inform regulations, and aid development of effective monitoring and detection methodologies for BC and beyond. © 2019 Society of Chemical Industry and John Wiley & Sons, Ltd.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".