Pore-Scale Observation of Solvent Based Foam During Heavy Oil Recovery
Bibliographic record
Abstract
Abstract Aqueous based foam injection has gained interest for conventional oil recovery in recent times. Foam can control the mobility ratio and improve the sweep efficiency in oil reservoirs over gas flooding. However, due to the high viscosity of oil, its application in heavy oil reservoirs is challenging. Moreover, oil-wet nature of carbonate reservoirs makes it difficult for aqueous based foam to efficiently remove the heavy oil. On the other hand, hydrocarbon solvents have been used for decreasing the heavy oil viscosity and increase its recovery by diffusion and mixing mechanisms. However, low rate of diffusion/dispersion and inadequate sweep efficiently, especially in heterogeneous reservoirs, are of the main challenges during solvent injection. Combination of foam and solvent (solvent based foam) can overcome the challenges existing in the separate application of aqueous based foam and solvent injection for heavy oil recovery. The challenge is to understand how the combination of solvent and foam will help us to improve the heavy oil sweep efficiency. This paper introduced a new approach to increase sweep efficiency during heavy oil recovery with the help of hydrocarbon solvent-based CO2 foam. Foam was generated with the help of a fluorosurfactant in the hydrocarbon solvent. Static bulk performances of foam were analyzed at different concentrations of surfactant. Surface tension measurement was also performed to study the adsorption of surfactant into the liquid-gas interface and its effect on foamability and foam stability. A specially designed fractured micromodel (oil wet, representing fractured carbonate reservoirs) were used to visualize the pore scale phenomena during solvent based foam injection. A high quality camera was utilized to capture high quality images/movies. According to static experiments, although the value of the surface tension of hydrocarbon solvent was initially low, the addition of surfactant slightly decreased the surface tension further and surfactant adsorption at the interface improved the foam stability. This process was more evident in higher concentration of surfactant. In addition, dynamic pore scale observation through this study revealed that solvent based foam can significantly contribute to heavy oil recovery with different mechanisms. At initial stage, solvent diffuses and mixes with viscous oil and reduce the viscosity. Later, foam bubbles improve the sweep efficiency by diverting the solvent toward untouched part of the porous media. In addition, foam bubbles partially blocked the opening area in matrix/swept-area increasing the contact of solvent and heavy oil, providing better mixing. Therefore, oil is swept much faster and more efficiently from the grain in oil-wet porous media compared to that of conventional solvent flooding. Successful application of solvent based foam can significantly improve the heavy oil recovery in reservoirs with high heterogeneity and oil-wet matrix. Cooperation of diffusion/dispersion and mobility reduction will result in faster oil production and lesser amount of oil will leave behind improving the sweep efficiency.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".