Effect of Initial Gas Saturation on Steam Assisted Gravity Drainage Process
Bibliographic record
Abstract
Abstract Cold Heavy Oil Production with Sand, CHOPS, is a primary recovery method commonly used in many Canadian heavy oil reservoirs. In spite of its commercial success, the oil recovery factors achievable with this process range between 5 to 20 percent. In order to recover more oil from primarily depleted reservoirs, Steam Assisted Gravity Drainage (SAGD) process can be considered. However, the performance of SAGD process is likely to be negatively affected by the initial gas saturation present in such depleted reservoirs. Unfortunately, no systematic study of the effect of initial gas saturation on SAGD performance has been reported. This paper presents an experimental evaluation of the effect of initial gas saturation on SAGD performance using physical models. Different gas saturation levels were established in the model by modifying the model packing and saturating techniques. High pressure physical model experiments were carried out by injecting steam at controlled rate and producing the oil from the production well at constant pressure. The oil production behavior was analyzed to evaluate the effect of initial gas saturation on thermal efficiency of the process. Based on the results, it is possible to conclude that initial gas saturation of about 9 percent, or higher, accelerated heat dissipation and retarded the formation and growth of the steam chamber. Due to the higher relative permeability of steam in the gas saturated zone, it becomes difficult to confine the steam in a chamber as seen in the conventional SAGD. The temperature in the steam zone was noticeably below the steam saturation temperature and the oil production rate was substantially lower compared to similar test without the gas saturation. The results strongly suggest that SAGD would not be a viable option in Heavy oil reservoirs containing high free gas saturations.
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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 | 0.001 |
| 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".