Determination of Individual Diffusion Coefficients of Solvent/CO2 Mixture in Heavy Oil With Pressure-Decay Method
Bibliographic record
Abstract
Summary A novel methodology was developed to determine the molecular-diffusion coefficient for each component of the solvent/CO2 mixture in heavy oil under reservoir conditions on the basis of the pressure-decay theory. Experimentally, molecular-diffusion tests for the solvent/CO2/heavy-oil systems (i.e., pure-CO2/heavy-oil system, C3H8/CO2/heavy-oil system, and n-C4H10/CO2/heavy-oil system) are performed with a DBR pressure/volume/temperature system at constant temperature and decayed pressure. Theoretically, the Peng-Robinson equation of state combined with a 1D diffusion model is developed to describe the diffusion process of solvent/CO2 mixture in heavy oil. The composition analysis in the beginning and the end of pressure-decay experiments for the solvent/CO2/heavy-oil system indicate that the gas-phase solvent fraction decreases as diffusion proceeds, whereas the gas-phase CO2 fraction increases during the tests. One can determine the individual molecular-diffusion coefficient for each component in the mixture by minimizing the discrepancy between the measured composition change and the calculated composition change with the diffusion model. The newly developed methodology is successfully validated with the diffusion tests on the two solvent/CO2 mixtures: C3H8/CO2/heavy-oil system and n-C4H10/CO2/heavy-oil system. As for the solvent/CO2 mixtures tested, the molecular-diffusion coefficient of solvent in heavy oil is found to be significantly larger than that of CO2 in heavy oil. At similar test conditions, the C3H8/CO2/heavy-oil system ends up with a swelling factor of 1.058 after 168 hours of diffusion test, in comparison to 1.031 for the CO2/heavy-oil system.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".