Experimental and Numerical Study of VAPEX at Elevated Temperatures
Bibliographic record
Abstract
Abstract Incorporating some heat injection along with the solvent injection appears to be the most viable option for improving the drainage rate of VAPEX in extra-heavy oil formations. The obvious question then concerns the magnitude of temperature increase needed to make the drainage rate economical. The objective of this work was to examine the effect of temperature on VAPEX performance. VAPEX experiments under different operating conditions were conducted in a high-pressure physical model. Physical model was packed with 250 Darcy sand and saturated with Athabasca bitumen (Mackay River oil). Injecting propane at 0.817 MPa, temperatures from 40 to 60ºC were tested to investigate possible improvement to oil production rates. Experimental results were numerically simulated with a commercial compositional simulator, Computer Modelling Group's (CMG) GEM. CMG's WinProp module, along with available experimental data, was employed to model the phase behavior and properties of the propane / Athabasca bitumen system. By history matching the experimental production data, results were extended to wider ranges of temperature and VAPEX performance at elevated temperatures was investigated. According to the results, substantial improvement in the performance of VAPEX in reservoirs containing this type of oil would require increasing the reservoir temperature above 60ºC.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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 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".