Modelling Mass Transfer Boundary Layer Instability in the CO-Based VAPEX Process
Bibliographic record
Abstract
Abstract VAPEX (vapour extraction) is a promising technique for the recovery of heavy oil and bitumen reservoirs, especially for cases where steam-assisted gravity drainage and other thermal recovery methods are not economical. In the VAPEX process, a solvent is injected into the reservoir to reduce the oil viscosity and mobilize it towards the production well. CO2-based VAPEX is an attractive option from both economic and environmental perspectives. In CO2-based VAPEX, unlike other hydrocarbon solvents, dissolution of CO2 into the oil can result in a density increase of the diluted oil. As a consequence, the diluted oil has a higher density than the immobile oil beneath and a gravitationally unstable diffusive boundary layer is induced, which may lead to natural convection. In this study, a mathematical model for the diffusive boundary layer in the CO2-oil contact region in the VAPEX process is developed and the possibility of convective mixing occurrence is examined using linear stability analysis, based on the amplification of the initial velocity perturbations. It is found that in field-scale cases in the VAPEX process, the Rayleigh number is much smaller than the critical Rayleigh number, (Rac), and natural convection cannot happen in this process. Introduction The world's total reserve of heavy oil and bitumen is about six trillion barrels, which is about six times the amount of conventional resources(1). A major part of these resources are in Canada, Venezuela and the United States. Most of these reserves are at such depths that open-pit mining cannot be used economically, and in situ methods have to be used to reduce the viscosity of the oil-in-place and mobilize it. Either thermal methods or non-thermal methods can be used to recover these reserves. The viscosity of oil is a strong function of temperature and decreases sharply with increasing temperature. Currently steam-assisted gravity drainage (SAGD), a thermal method, is a popular scheme for the recovery of heavy oil and bitumen and has been successfully applied in several fields. Despite the success of this process for some reservoirs, there are many reservoirs that SAGD cannot be applied due to excess heat loss, which makes it uneconomical to operate. In thin reservoirs, the need for steam increases and the steam-to-oil ratio (SOR) is prohibitively high. Many oil and bitumen reservoirs have a bottom aquifer, and heat loss to the water can make the process unfeasible(2). There are also reservoir conditions where SAGD may not be applied, such as when water saturation is high or porosity is low. In cases where SAGD cannot be applied, VAPEX is an option for the recovery of these resources. The initial development of the VAPEX process was first introduced by Butler and Mokrys(3) as a solvent analogue to steam-assisted gravity drainage. The steam chamber in SAGD is replaced by a solvent chamber in VAPEX. In the VAPEX process, a solvent is injected near its dew point (where both solubility and diffusivity of the vapour solvent into oil are at their maximums) and forms a solvent chamber within the reservoir(4).
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".