Numerical Simulation of Gas Mobility Control by Chemical Additives Injection and Foam Generation during Steam Assisted Gravity Drainage (SAGD)
Bibliographic record
Abstract
Gas mobility control is highly required to obtain a sufficiently-expanded and uniformly-developed steam chamber, which is conducive to steam-assisted gravity drainage (SAGD) production. Adding chemical additives with in-situ generation of foam (CAFA-SAGD) is an approach to improve sweep efficiency, displace residual oil and reduce heat loss, enhancing SAGD performance in terms of both oil production and steam oil ratio (SOR). With the input of the obtained chemicals and foam parameters and the consideration of the principle mechanisms (steam foam mobility control and IFT reduction), it depicts the dynamic distribution of components and compares the performance of CAFA-SAGD and SAGD with numerical simulation. Foam generation and foam collapse are also incorporated. Simulation study demonstrates that steam mobility control is conducive to generate a larger oil displacement area in the lower part of the model. Also, residual oil is more depleted owing to higher injection pressure and interfacial tension reduction. The optimization from this study ensures that the oil recovery factor is improved by 5.34%.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".