Effect of Wells’ Connectivity Enhancement on the Performance of Vapor Extraction (VAPEX) Process
Bibliographic record
Abstract
Drawbacks of the thermal recovery techniques such as excessive heat loss to the surrounding formations and carbon dioxide emissions during these processes have directed the interests of researchers towards more viable alternatives such as solvent-based recovery techniques (e.g. VAPEX). One of the key parameters to implement a successful VAPEX process is to control the profiles of vapour chamber and consequently improve the areal sweep efficiency. In this regard, an optimum well configuration and well connectivity establishment between the injection and production wells are desirable. The main focus of this research is to extensively conduct series of experiments to investigate the effect of injection/production wells connectivity on the performance of VAPEX process. For this purpose, two large-scale physical models were employed. Propane and propane/carbon dioxide mixtures were selected as the injection solvents in the visual sand-packed physical models saturated with heavy oil sample from Saskatchewan (Canada) heavy oil. Various injection/production scenarios were followed and it was found that the initial connection path between the injector and producer had a significant impact on the vapour chamber profiles and consequently on the ultimate recovery performance of the VAPEX process.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".