Generalized Approach to Predict k-Values of Hydrocarbon Solvent/Bitumen Mixtures
Bibliographic record
Abstract
Abstract A generalized model is presented to calculate the k-values of methane/bitumen, ethane/bitumen, propane/bitumen, and butane/bitumen systems. These data are required for phase behaviour modeling and simulation of solvent-aided bitumen recovery processes. The proposed model is evaluated by comparing the calculated results with the measured experimental k-values. The proposed model provides generalized binary interaction parameters between each hydrocarbon solvent (methane, ethane, propane, and butane) and the defined components in bitumen and calculates the k-values of solvent/bitumen systems. Unlike the existing common approaches, experimental solubility data are not required to tune the model. The boiling point or carbon number distribution of bitumen or heavy oil obtained by simulated distillation (SimDist) test is the only required data to characterize and define the components of heavy oil or bitumen. The SimDist test is a very fast test and much less expensive than the common solubility measurements. This model has been developed based on the experimental fractionation of bitumen. The Athabasca bitumen was experimentally fractioned to four bitumen cuts applying vacuum distillation method and the solubility of solvent in each bitumen cut were measured at wide ranges of temperature and pressure. The measured solubility data of methane, ethane, propane, and butane in each bitumen cut have been used to tune the PR-EoS and the generalized binary interaction parameter coefficients for each solvent and bitumen components have been found. To calculate the k-values of solvent/bitumen mixtures, the bitumen is defined as a mixture of n-alkanes based on simulated distillation results. The properties of n-alkanes have been assumed for each component. Employing the obtained binary interaction parameters in PR-EoS using experimental data of solvent/bitumen cut systems and considering the defined bitumen components as input to the proposed model, the k-values of solvent and any bitumen or heavy oil mixtures are calculated. The validity of the proposed model has been confirmed by calculating the k-values of methane, ethane, propane, and butane with two different bitumen samples with an average deviation of less than 3.0 %. The proposed model predicts the k-values of methane/bitumen, ethane/bitumen, propane/bitumen, and butane/bitumen mixtures without requiring the time and cost intensive experimental PVT data for tuning. Providing the simulated distillation results of any bitumen or heavy oil samples, the k-values of hydrocarbon solvent/bitumen or heavy oil can be calculated in wide ranges of temperature and pressure. The outputs of this model can be directly used as k-values in simulation of solvent-aided thermal recovery processes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".