Compositions and greenhouse gas emission factors of flared and vented gas in the Western Canadian Sedimentary Basin
Bibliographic record
Abstract
UNLABELLED: A significant obstacle in evaluating mitigation strategies for flaring and venting in the upstream oil and gas industry is the lack of publicly available data on the chemical composition of the gas. This information is required to determine the economic value of the gas, infrastructure and processing requirements, and potential emissions or emissions credits, all of which have significant impact on the economics of such strategies. This paper describes a method for estimating the composition of solution gas being flared and vented at individual facilities, and presents results derived for Alberta, Canada, which sits at the heart of the Western Canadian Sedimentary Basin. Using large amounts of raw data obtained through the Alberta Energy Resources Conservation Board, a relational database was created and specialized queries were developed to link production stream data, raw gas samples, and geography to create production-linked gas composition profiles for approximately half of the currently active facilities. These were used to create composition maps for the entire region, to which the remaining facilities with unknown compositions were geographically linked. The derived data were used to compute a range of solution gas composition profiles and greenhouse gas emission factors, providing new insight into flaring and venting in the region and enabling informed analysis of future management and mitigation strategies. IMPLICATIONS: Accurate and transparent determination of environmental impacts of flaring and venting of gas associated with oil production, and potential benefits of mitigation, is severely hampered by the lack of publicly available gas composition data. In jurisdictions within the Western Canadian Sedimentary Basin, frameworks exist for regulating and trading carbon offset credits but current potential for mitigation is limited by a lack of standardized methods for calculating CO2 equivalent emissions. The composition and emission factor data derived in this paper will be useful to industry, regulators, policy researchers, and entrepreneurs seeking statistically significant and openly available data necessary to manage and mitigate upstream flaring and venting activity and estimate greenhouse gas impacts.
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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 | 0.003 | 0.005 |
| 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".