Effect on Non-condensable Gas on Solvent-Aided SAGD Processes
Bibliographic record
Abstract
Abstract Steam Assisted Gravity Drainage (SAGD) is the preferred in-situ technology to recover heavy oil and bitumen from Canadian reservoirs. It is commercially proven, delivers high oil rates and high ultimate recoveries. Given the large energy requirement and the volume of emitted greenhouse gases from SAGD process, there is a strong motivation to develop enhanced oil recovery processes with lower energy and emission intensities. Addition of suitable alkane solvents to steam in processes such as ES-SAGD can reduce the use of energy and green-house emissions in SAGD. Potential hydrocarbon additives provide an additional means to raise oil phase mobility beyond that achieved by heat. The Athabasca reservoir contains small amounts of initial solution gas which is negligible compared to conventional oil reservoirs, however, even small amounts of solution gas might play an important role in thermal processes driven by gravity drainage. In majority of experimental and simulation study of Solvent-Assisted SAGD processes carried out, initial solution gas is not included. In this study, extensive simulation study is performed to understand the mechanism of solvent addition to SAGD process when initial solution gas is present. Simulation results show that initial solution gas reduces the oil recovery by SAGD process especially in Athabasca reservoir. A varying thickness non-condensable gas layer impedes heat transfer from the condensing steam to the bitumen zone. Hydrocarbon additives are not very effective in the presence of high initial solution gas ratio. Exsolved solution gas causes early condensation of steam and additives. As a result, hydrocarbon additives have diminished opportunities to contact bitumen and are unable to create a high oil phase mobility zone. In addition, a number of simulations are conducted to understand the role of operating pressure and pressure imbalance between SAGD well pairs. The difference between the operating pressure of adjacent SAGD well-pairs can be used to remove accumulated solution gas from the steam chamber.
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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 | 0.000 |
| 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) | 0.003 | 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".