Bibliographic record
Abstract
Solvent-based nonthermal heavy oil recovery methods are relatively new and still under development. The central idea in such techniques is to rely on solvent dissolution for viscosity reduction instead of heating. Among the solvent-based methods, VAPEX appears to be the most promising. In thin heavy oil and bitumen reservoirs, where the thermal processes are likely to fail due to excessive heat losses, VAPEX can be more successful. Nonetheless, the economic viability of VAPEX remains uncertain due to lower oil production rates predicted by scale-up of laboratory model results using the transmissibility based scaling criteria. However, such scaling is far from reality, and our previous experimental work [Yazdani and Maini. SPE Reservoir Eng. Eval. 2005, 8, 205−213] has shown that it underestimates the field rates. This paper presents the design of a very large physical model as well as the results of a set of VAPEX experiments carried out in this model. The results are, interestingly, in very good agreement with the trend of the previous experiments conducted by the authors [Yazdani and Maini. SPE Reservoir Eng. Eval. 2005, 8, 205−213] in smaller models. The results from this large model were combined with the previous results to improve the previously reported empirical scale-up correlation.
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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".