Phase Behaviour and Physical Properties of Dimethyl Ether DME/CO2/Water/Heavy Oil Systems under Reservoir Conditions
Bibliographic record
Abstract
Abstract In this paper, techniques have been developed to quantify phase behaviour and physical properties including phase boundaries, swelling factors, and phase volumes for reservoir fluids containing polar components from both experimental and theoretical aspects. Experimentally, a total of five pressure-volume-temperature (PVT) experiments including three sets of DME/CO2/heavy oil systems and two sets of DME/CO2/water/heavy oil systems have been carried out to measure saturation pressures, phase volumes, and swelling factors by using a versatile PVT setup. Theoretically, the modified Peng-Robinson equation of state (PR EOS) incorporated with the Huron-Vidal mixing rule and the Péneloux volume-translation strategy is employed as the thermodynamic model to perform phase equilibrium calculations. It is observed that the experimentally measured saturation pressures of DME/CO2/water/heavy oil mixtures are higher than those of DME/CO2/heavy oil mixtures at the same temperature and same molar ratio of solvents and heavy oil, owing to the fact that more water molecules can be evaporated into vapour phase. The binary interaction parameters (BIPs) between DME/heavy oil and CO2/DME pair, which are obtained by matching the measured saturation pressures of DME/CO2/heavy oil mixtures, work well for DME/CO2/heavy oil mixtures in the presence and absence of water. In addition, a swelling effect of heavy oil can be enhanced by adding the DME and CO2 mixtures compared to only DME or CO2. The new model developed in this work is capable of accurately reproducing the experimentally measured multiphase boundaries, swelling factors, phase volumes with a root-mean-squared relative error (RMSRE) of 4.68%, 0.71%, and 9.35%, respectively, indicating that it can provide fundamental data for simulating, designing, and optimizing the hybrid solvent-thermal recovery processes for heavy oil reservoirs.
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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".