Extension of Das and Butler Semianalytical Flow Model
Bibliographic record
Abstract
Summary In this work, the Das and Butler flow model was extended to account for the effect of differential pressure across a laterally and vertically spaced horizontal injection- and production-well pair for solvent vapour extraction (SVX) processes. The extended model provides a more-rigorous dispersion-coefficient correlation using interstitial pore velocity and mean particle size. This was used to history match oil-production data from 3D-scaled physical model experiments and to determine the effective dispersion coefficient of the solvent in heavy oil. The SVX experiments were performed with two model sizes and three different permeabilities spanning than two orders of magnitude. Laterally spaced horizontal wells were used to inject an 86:14 mol% mixture of butane and methane, respectively, as a dense vapour. The average dispersion coefficient of solvent (butane) was found to decrease with injected cumulative solvent and increase with reduction in permeability, and both of these relationships could be approximated with an inverse power function.
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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 | 0.002 | 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".