INVESTIGATION OF THREE-PHASE RELATIVE PERMEABILITIES FOR HEAVY OIL SYSTEMS USING SIMULATED ANNEALING TECHNIQUE; EFFECT OF OIL VISCOSITY
Bibliographic record
Abstract
Three-phase relative permeabilities play a crucial role in simulation of thermal heavy oil recovery processes. Obtaining such data is considerably challenging due to the tedious nature of experiments and accuracy of the results. A simulated annealing technique was used to estimate three-phase relative permeabilities in the form of isoperms by utilizing two-and three-phase displacement experiments conducted with a Berea core/heavy oil/brine/CO2 system. After validation of the technique using results obtained from steady-state experiments, the effect of oil viscosity on the three-phase relative permeability was investigated. Results of this study showed that, in a ternary diagram, the three-phase flow zone shifted toward the higher saturations of oil, while no significant change in the size of the three-phase flow zone occurred. Different curvatures were observed for relative permeability isoperms of each phase, indicating dependency of relative permeability to saturation of all phases. Increasing oil viscosity from 1174 to 2658 cP resulted in a decrease in the relative permeability in each phase. Results also indicated that, due to significant difference between the viscosity of the phases, oil relative permeability values are higher than those of brine and CO2 on the order of magnitude of three and five, respectively.
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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) | 0.000 | 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 | 0.001 |
| 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 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".