Effect of Viscosity and Diffusion Coefficient on the Kinetics of Bubble Growth in Solution-Gas Drive in Heavy Oil
Bibliographic record
Abstract
Abstract Some of the heavy oil reservoirs in Alberta and Western Saskatchewan show anomalously high primary recovery and high flow rate under solution gas drive. Several theories have been proposed for the anomalous behaviour. However, only a few theories look at the basic physics of the problem and find out the reason for this favourable behaviour. The process of solution gas drive involves nucleation of gas bubbles followed by bubble growth and finally flow of gas. In his work, the aspect of bubble growth is studied in heavy oil and in light oil. A numerical model is developed, including the hydrodynamic and mass transfer effects to investigate the effect of viscous and diffusional forces on bubble growth. An objective of the paper is to show that the effect of oil viscosity on bubble growth might be insignificant, even for heavy oils. A secondary objective is to examine the validity of the popular rowth model of R(t) = atb, when both diffusional and hydrodynamic forces are acting. The case of a gradual decline in pressure is studied, which more closely simulates the reservoir condition, and is compared with a step decline in pressure. It is found that the constants a and b in the above model need to be found for the conditions of interest; they depend on oil-type, rate of pressure drop, mass transfer boundary condition, etc. In another part of the paper, the gas phase growth during the solution gas drive experiment is modelled and the effect of various parameters, such as viscosity, depletion rate and diffusion coefficient, on the process is studied. It is found that, in a constant volumetric rate of depletion process, the system compressibility might remain unchanged for some time, even after bubbles have nucleated and while they are growing. Hence, the maximum supersaturation observed does not have to correspond with the nucleation pressure. Introduction The process of solution gas drive involves nucleation of bubbles in oil as the pressure falls below the bubblepoint pressure, following which the bubbles grow. During growth, the bubbles come in contact with each other and, with the breaking of the lamella, coalesce to form interconnected gas bubbles, often with multiple branches. The process of solution gas drive in heavy oil reservoirs shows a number of anomalies when compared to that in a light oil reservoir. A number of theories(1-7) have been proposed to explain this behaviour of the heavy oil reservoir. However, only a few look at the basic physics of the problem. In this paper, an attempt has been made to study bubble growth with specific application to the solution gas drive process by looking at the physics of bubble growth and study the effect of viscosity and other parameters. As a first step, a single bubble growth in bulk is considered and the effect of the porous medium is not included. The bubble growth in light oil, is compared with that in heavy oil, and the reason for the differences sought.
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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 | 0.002 | 0.001 |
| 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) | 0.000 | 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".