Enhanced Swelling Effect and Viscosity Reduction of Solvent(s)/CO2/Heavy-Oil Systems
Bibliographic record
Abstract
Summary In this paper, techniques have been developed to examine the enhanced swelling effect and viscosity reduction of CO2-saturated heavy oil with the addition of either solvent C3H8 or solvent n-C4H10. Experimentally, pressure/volume/temperature (PVT) tests are conducted to measure the saturation pressure, swelling factor, and viscosity of the C3H8/heavy-oil system, the C3H8/CO2/heavy-oil system, and the n-C4H10/CO2/heavy-oil system, respectively, in the overall temperature range of 280.45 to 391.55 K. It has been found that an increased swelling effect of heavy oil is obtained by adding the gas solvent C3H8 or n-C4H10 into the CO2 stream. An enhanced viscosity reduction of the CO2/heavy-oil system is also achieved in the presence of either C3H8 or n-C4H10. The enhanced swelling effect and viscosity reduction caused by adding either C3H8 or n-C4H10 into the CO2 stream are particularly favorable for achieving a higher heavy-oil recovery compared with pure-CO2 processes. Theoretically, three binary-interaction-parameter (BIP) correlations in the Peng-Robinson (PR) equation of state (EOS) (PR-EOS) method have been proposed for respectively characterizing CO2/heavy-oil binaries, C3H8/heavy-oil binaries, and n-C4H10/heavy-oil binaries by treating each oil sample as a single pseudocomponent with its molecular weight (MW) and specific gravity (SG). The BIP correlations (together with the PR-EOS) can be used to predict the saturation pressures and swelling factors of the C3H8/CO2/heavy-oil system and the n-C4H10/CO2/heavy-oil system with a generally good accuracy.
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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".