Interplay of Capillarity, Drainage Height, and Aqueous Phase Saturation on Mass Transfer Rate of Solvent Vapor into Heavy Oil
Bibliographic record
Abstract
Abstract Performance of the vapor extraction process is strongly dependent on the efficiency of the mass transfer rate between the solvent and heavy oil or bitumen. Therefore, realistic approximation of diffusion and convective dispersion occurring on the edge of the vapor chamber is required for reliable prediction of production rates in this process. Studies conducted at extremely high permeabilities (>200 D) have reported up to four orders of magnitude increase in the solvent diffusion/dispersion rates between the solvent and heavy oil, such increases could result in unrealistic overestimation of the performance of this process at real reservoir conditions. To address this shortcoming, a comprehensive experimental study was designed and conducted to systematically investigate the interplay of capillarity, drainage height, and aqueous phase saturation on efficiency of mass transfer rate in permeability range similar to western Canadian heavy oil and bitumen reservoirs (i.e. 5.1–6.5D). In order to experimentally simulate the vapor extraction process, a new experimental approach was developed to eliminate the effect of pressure disturbances occurring during the course of experiment (20–45 days) and investigate the interplay between studied parameters in a gravity dominant system. In this study, measured stabilized drainage rates per unit length of porous media (9.17×10-7-3.33×10-5 cm3/s/cm) revealed functionality with drainage height, specific pore surface area of the porous medium, and presence of aqueous phase at higher capillarities. Moreover, analytical modeling was conducted to determine the effective diffusion/dispersion coefficient, which showed convective dispersion is not playing a prominent role in mixing between solvent and heavy oil as it was proposed by studies conducted in high permeabilities. In addition, comparison between the stabilized drainage rates of oil in absence or presence of water saturation confirmed that the presence of water phase enhances the drainage rates at higher capilarities, which is in contradiction with previous studies investigating the effect of aqueous phase saturation on mass transfer rate in higher permeabilities. This paper provides in-depth knowledge of the impact of three major parameters that affect the rate of the mass transfer between heavy oil and solvent, and that are necessary for realistic modeling of the performance of the vapor extraction process.
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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 | 0.000 |
| 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 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".