Comprehensive Multi-Stage Analytical Treatment of Steam-Assisted Gravity Drainage SAGD
Bibliographic record
Abstract
Abstract A comprehensive analytical model of the Steam-Assisted Gravity Drainage (SAGD) process is developed, encompassing steam chamber rise, sideways expansion, and the confinement phases. Results are validated using experimental and field data. A new analytical model for predicting steam chamber rise velocity and oil production rate during this period is developed. In this theory, by combining volumetric oil displacement with Darcy oil rate considering the indirect frontal instability effect, the rise velocity, and the steam chamber height are calculated. The model is extended to predict oil production, heat or steam injection rate, heat consumption and Cumulative Steam-Oil Ratio (CSOR) during this phase. The model results show the CSOR decreases, with an increasing oil production rate. The rise velocity increases with an increase in permeability and temperature. Results are validated with experimental and field data. The sideways steam chamber expansion is treated by a new analytical approach which is called Constant Volumetric Displacement (CVD) where injection rate must be increased continuously for a constant oil rate. At the final stage, adjacent chambers interfere, reducing the effective head for gravity drainage and the heat requirement in this system. For a small well spacing, confinement occurs earlier, heat loss starts decreasing sooner, resulting in a lower CSOR, than for a large spacing. The above analytical SAGD models including rise, lateral spreading, and confinement phases are combined to obtain the Comprehensive Constant Volumetric Displacement (CCVD) model. The results are validated against experimental and field data. Excellent agreement was obtained with laboratory and field results.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".