Polymer/Gel Enhanced Foam Flood for Improving Post-Waterflood Heavy Oil Recovery
Bibliographic record
Abstract
Abstract Due to its low cost, excellent injected performance and good blocking capacity for high permeability zones, polymer/gel enhanced foam flood has been proven as an efficient method to improve oil recovery. This paper presents an optimization study of the slug size of polymer enhanced foam (preformed foam) and a study of gel-enhanced foam on oil recovery and high permeability zone blocking for a Saskatchewan heavy oil. A series of sandpack tests with different slug sizes are conducted to investigate the oil recovery performance of polymer enhanced foam flood. The experimental results indicate that, by considering the foam flood efficiency, the optimal slug size of polymer enhanced foam flood is 1.5 PV in this study. For gel enhanced foam flood, the single-sandpack tests suggest that the gel enhanced foam flood and extended waterflood can still significantly improve the oil recovery (up to 24.1%) after polymer enhanced foam flood; the parallel-sandpack test indicates that gel-foam can efficiently promote the oil recovery in the lower permeability layer by modifying the injection profile. In summary, gel enhanced foam can be used as the fourth recovery method for heavy oil reservoirs after initial waterflood and polymer enhanced foam flood.
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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) | 0.001 | 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".