Effect of CO2 on Heavy Oil Recovery and Physical Properties in Huff-n-Puff Processes Under Reservoir Conditions
Bibliographic record
Abstract
In this paper, experimental and numerical techniques have been utilized to quantify heavy oil properties in CO2 huff-n-puff processes under reservoir conditions. Experimentally, fluid properties together with viscosity reduction of heavy oil and interfacial properties between CO2 and heavy oil have been quantified, while five cycles of CO2 huff-n-puff processes have been conducted to determine oil recovery together with component variation of produced and residual oils. Theoretically, numerical simulation has been conducted to analyze the underlying recovery mechanisms associated with the CO2 huff-n-puff processes. CO2 huff-n-puff processes are only effective in the first two cycles under the existing experimental conditions, while the effective sweep range is limited near the wellbore region, resulting in poor oil recovery in the subsequent cycles. As for produced oil, its viscosity, density, resin and asphaltene contents, and molecular weight of asphaltene are reduced, whereas, for the residual oil, they are increased. The asphaltene component in the residual oil shows weak stability compared to that of the produced oil, while the ultimate oil recovery after the fifth CO2 cycle of huff-n-huff processes is measured to be 31.56%.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".