An Evaluation of Air Injection as a Follow-Up Process to Cyclic Steam Stimulation in a Heavy Oil Reservoir
Bibliographic record
Abstract
Abstract The majority of bitumen and extra heavy oil is produced by steam-based recovery processes yet these methods are energy intensive and emit large amounts of greenhouse gas to the atmosphere. Not only is the emissions intensity high due to steam generation, but also the water handling and treating facilities required for these recovery methods is expensive both to purchase and install but also to operate. A lot of focus of research has been on reduced steam processes, such as thermal-solvent techniques, as well as in situ combustion technologies such as Air Injection. Here, air injection is evaluated as a follow-up process to Cyclic Steam Stimulation in a deep thick heavy oil reservoir. The reservoir simulation model is obtained from a history-match to existing cyclic steam stimulation (CSS) field data. The results demonstrate that an additional 33% oil recovery is reached by using an air injection follow-up process. This gives a total recovery factor equal to about 55%. Based on incremental cumulative energy-to-oil ratio, the results suggest that air injection follow-up processes should be considered for post-CSS operations but that further improvement of the energy intensity is needed.
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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 | 0.000 |
| 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) | 0.002 | 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".