Prediction of solubility of CH<sub>4</sub>, C<sub>2</sub>H<sub>6</sub>, CO<sub>2</sub>, N<sub>2</sub> and CO in bitumen
Bibliographic record
Abstract
Abstract An accurate model to calculate the solubility of light hydrocarbons (methane, CH 4 and ethane, C 2 H 6 ) and non‐hydrocarbon gases (carbon dioxide, CO 2 , nitrogen, N 2 and carbon monoxide, CO) in bitumen is required for the optimal design of bitumen and heavy oil recovery processes and transportation. In this work, we used the Krichevsky–Ilinskaya equation to predict the solubility of light solvents (CH 4 , C 2 H 6 , CO 2 , N 2 and CO) in bitumen from five reservoirs in Alberta, Canada. The Peng–Robinson (PR) equation of state (EoS) is used to treat the gas phase. The proposed model is then verified using available experimental solubility data of light solvents in bitumen, and good agreement is observed. The experimental data cover wide ranges of pressures and temperatures. The results show that the proposed model represents the available solubility data of light hydrocarbons (CH 4 and C 2 H 6 ) and non‐hydrocarbon solvents (CO 2 , N 2 and CO) in bitumen with absolute average relative deviations of <4.2% and 5.4%, respectively. These results can be applied to heavy oil and bitumen recovery processes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".