Solubility of carbon dioxide and ethane in <scp>Lloydminster</scp> heavy oil: Experimental study and modelling
Bibliographic record
Abstract
Abstract Heavy oil reserves in the world represent 5.5 trillion barrels, which are equivalent to five times the conventional crude oil reserves. Heavy oil reserves will be the main petroleum source for the world's future demand for energy. To enhance the recovery of heavy oil/bitumen, solvent‐based recovery seems to be one of the most promising alternatives to costly thermal methods. Phase behaviour studies of light gases in heavy oil are therefore very important when designing surface facilities and for enhanced oil recovery operations. In this study, we present solubility data for carbon dioxide and ethane in Lloydminster heavy oil. Measurements were carried out using a microbalance at 290.2, 298.2, and 313.2 K and at pressures varying from 200–2000 kPa. Experimental data were regressed with the Peng‐Robinson (PR) equation of state. We also report results of the fractionation of the heavy oil and its characterization in terms of SARA (saturates, aromatics, resins, and asphaltenes) fractions. Henry's law constants for gaseous solvents were also regressed and reported. As expected, ethane had a higher solubility than CO 2 in the heavy oil at all temperatures.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".