Life Cycle Assessment of Western Canadian Tight Oil Resources
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide In the past decade, Western Canada has seen the rapid growth of tight oil resource development, where the associated environmental impacts are still being understood. This study presents a comparative life cycle assessment (LCA) of 13 tight oil producing formations across British Columbia (BC), Alberta (AB), and Saskatchewan (SK). The 2017 oil-production-weighted average gasoline emissions intensity produced from tight oil in BC, AB, and SK (P10 to P90 ranges in the brackets) are 85.7 (83.3–88.4), 89.2 (84.3–138), and 111 (88.5–196) gCO 2 e/MJ-gasoline, respectively. Operational venting activities drive emissions intensities, particularly in SK. The emissions intensities of gasoline produced from the Montney (BC) and Montney (AB) formations are found to be some of the lowest in North America with averages of 85.7 (83.3–88.4) and 87.0 (84.3–91.0) gCO 2 e/MJ-gasoline. In 2017, an estimated 14.8 million tonnes of CO 2 e (MtCO 2 e) was emitted from upstream tight oil production activities (including preproduction, production, and transportation) in Western Canada. A spatiotemporal correlation shows that 1.3% of tight oil wells assessed over the period 2012 to 2017 were correlated to seismic events. Water use for hydraulic fracturing also demonstrates regionally dependent relative impact, as shown by impacts to water scarce regions of Southern AB and SK. While this analysis does not prove causation, it demonstrates LCAs can aid investigations on environmental trade-offs. The results show the complexity of relationships between physical characteristics, operational characteristics, and environmental performance metrics rather than point estimates of GHG emissions alone.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| 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) | 0.002 | 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".