Coupling of Solvent and Hot Water to Improve Heavy Oil Recovery: Experimental and Simulation Studies
Bibliographic record
Abstract
Abstract There are abundant heavy oil deposits characterized by shallow depth, thin pay zone, low porosity, and bottom water in Western Canada. These types of reservoirs are neither suitable for thermal heavy oil recovery techniques (e.g. SAGD) nor for solvent injection (e.g. VAPEX). Coupling of Solvent and Hot Water (CSHW) injection was proposed and examined as an alternative to improve the heavy oil recovery in these reservoirs. In this study, a series of core flooding tests and numerical simulations were conducted to investigate and evaluate the CSHW injection performance in thin heavy oil reservoirs containing oil with viscosity of around 1,000 to 6,000 cP. To identify the contribution of hot water and solvent as well as their effectiveness when they combined, three types of core flooding tests were performed individually using hot water, solvent, and CSHW injection. In addition, the effects of oil viscosity, water injection temperature (15°C, 24°C, 50°C, 65°C) and solvent (C1, C3, C1+C3) on oil recovery were examined. Moreover, effects of parameters such as injection rate, displacement volume, slug size, and injection pattern were also investigated. Furthermore, the core flooding tests were history matched based on the established numerical simulation model. The effects of temperature and solvent components on multi-phase fluid flow were examined through numerical simulation. As the result, the optimal CSHW injection parameters were screened based on experimental and numerical studies conducted. Results of this study showed that the oil recovery factor was enhanced by 19.1% when temperature of injection water increases from 24°C to 65°C. More importantly, it was found that the CSHW is a more feasible option that recovers higher amount of oil at lower cost when compared with pure solvent or hot water injection. In addition results indicated that if smaller slugs of hot water and solvent are injected, the recovery process is more efficient. In this particular study, injection of smaller slugs resulted in 53.5% recovery factor. These results indicate that the CSHW is a promising hybrid process for the heavy oil recovery which requires low facility investment.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| 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".