An Analytical Model to Predict Cumulative Steam Oil Ratio (CSOR) in Thermal Recovery SAGD Process
Bibliographic record
Abstract
Abstract This paper presents a simple yet sophisticated analytical model to predict cumulative steam oil ratio (CSOR) using the material/energy balance and gravity drainage theory, in which CSOR is a function of average reservoir properties (porosity, permeability, heat capacity, and thermal conductivity), and time-dependent variables (injection temperature, rising chamber height, chamber oil saturation, and producing fluid temperature) to mimic the practical SAGD process. This model has been applied to predict CSORs of the typical wells in the JACOS’ Hangingstone SAGD project. History match results show the reliability and accuracy of the model at different geological conditions. The analytical model has proven to be satisfactory to predict CSOR by reasonably adjusting a few reservoir parameters, such as formation permeability, effective net pay, and operational parameters.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".