An Ultra-low Emissions Enhanced Thermal Recovery Process for Oil Sands
Bibliographic record
Abstract
The growth of energy demand over the next few decades with declining conventional fossil fuel production implies that greater reliance will be placed on unconventional fossil fuel energy sources such as heavy oil and extra heavy oil (bitumen). However, unconventional fuels tend to have higher environmental impact than their conventional counterparts. Here, we focus on the oil sands resource of Alberta, Canada whose recovery is both energy and emissions intensive on one hand yet provide economic and social benefits to society on the other hand. There is a drive to improve the energy and emission intensities of oil sands recovery processes. We evaluate the combined application of natural gas decarbonization (NGD) with oxy-combustion and the utilization its CO 2 -rich flue gas to achieve an ultra-low emissions enhanced thermal recovery process for bitumen from oil sands. We used industry-accepted thermal reservoir simulation tools to model steam assisted gravity drainage (SAGD) bitumen recovery using a steam-CO 2 mixture. Our results show that the overall performance of the proposed process when applied to a moderately high oil saturation reservoir is improved over the current practice both from an energy intensity and a CO 2 footprint basis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".