A Calculation Model for Steam Property Variation Along Wellbore Trajectory in SAGD Processes
Bibliographic record
Abstract
Abstract Steam properties such as steam pressure and steam quality are critical parameters to form integrated steam chamber and control steam consumption cost during SAGD process. However, steam property variation along steam injection well was not well understood yet. In this paper, a model describing steam flow behavior in steam injection wellbore was built and solved; accordingly steam property variation along steam injection wellbore can be calculated. In our model, both vertical and horizontal wellbores were further divided into several segments. Mass, momentum and energy balance equations have been applied to steam flow inside each segment. During the derivation of these equations, a void fraction correlation that is based on flow-pattern-independent drift-flux model was applied to describe steam flow in a non-uniform manner. This model was validated by several sets of published field data and a series of general cases were studied to investigate the steam property variation inside wellbore. The computational results indicated that steam property distribution along vertical and horizontal wellbore portions have similar characteristics: steam pressure and steam quality tend to decrease along with wellbore trajectory in both vertical and horizontal wellbore portions during SAGD process; With the increase of steam injection pressure, steam quality decreases faster; with the increase of steam quality during injection, steam pressure decreases faster; With the increase of steam injection rate, steam pressure decrease faster while steam quality decrease slower. For horizontal wellbore, the increase of reservoir permeability tends to slow down the steam pressure decrease but accelerates steam quality deterioration; the increase of oil viscosity tends to slow down the steam quality deterioration but accelerate steam pressure decrease. The results from this study show the effects of steam properties varying along wellbore trajectory under different steam injection conditions and can be used as a design guidance to optimize the steam injection practice in SAGD process.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".