Carbon intensity of in-situ oil sands operations with direct contact steam generation lower than that of once-through steam generation
Bibliographic record
Abstract
The oil sands resource in Western Canada are a considerable energy asset for Canada, but the energy and emissions intensities of producing this petroleum resource are substantially worse than that of conventional petroleum resources. With requirements for carbon-intensity reduction, new, less emissive recovery processes must be developed to enable continued production and cash flow from this important resource. The largest source of carbon emissions on in-situ in oil sands recovery processes, such as Steam-Assisted Gravity Drainage (SAGD), is steam generation, where natural gas is combusted. An alternative to conventional steam generation is Direct Contact Steam Generation (DCSG), where steam is generated in the combustion flame, and with rich oxygen combustion, the steam plus carbon dioxide mixture is injected into the reservoir. We explore the carbon intensity of DCSG and compare it to existing once-through steam generation using life cycle analysis. The results reveal considerable environmental benefits with nearly 30% emission reduction when applying a DCSG in SAGD instead of an OTSG. The results suggest that oil sands operators could improve their emissions intensity significantly if they adopted DCSGs in their operations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".