Bibliographic record
Abstract
Summary The vapour extraction (VAPEX) process and its many hybrid variants have attracted a great deal of attention as potentially lessenergy-intensive alternatives for exploiting heavy-oil and bitumen resources. However, despite significant work over the past 2 decades, uncertainty remains about the basic mechanisms, the scaling aspects, and the most appropriate methods of numerically simulating these processes. This paper offers some insights into several of these outstanding questions. The questions are examined in the context of an extensive and well-documented set of VAPEX experiments carried out by Maini and his colleagues over the past 10 years. We have experimented with different methods of simulating these experiments using a physics-based reservoir simulator. Despite the high permeability (greater than 200 darcies in all of the experiments), we find that capillary pressure plays a significant role in the drainage. The simulations suggest that most of the drainage takes place in the capillary transition zone along the edge of the vapour chamber, rather than in the single-phase zone ahead of it which has not yet been contacted by vapour. It has been emphasized in the literature that the near-linear scaling of oil rate with height observed in the experiments is dramatically different from the square-root-of-height dependence predicted by the original analytic model of VAPEX. However, the experiments also show an increasing solvent fraction in the produced-oil phase as height increases. When this "solvent mixing" effect is separated from the rates, the remaining height dependence is less than linear, though still greater than square root of height. The relative roles of molecular diffusion and mechanical dispersion in VAPEX have been discussed widely in the literature. Generally, mechanical dispersion is expected to play a larger role in these high-permeability experiments (compared with the field) because of larger fluid velocities. We present a method of inferring the diffusion/dispersion present in the simulations, despite a hidden component of numerical dispersion caused by the numerical method itself. We find that the experiments are well matched with values of diffusion and dispersion in line with literature correlations, and that the contribution of mechanical dispersion is perhaps not as large as might be expected relative to that of molecular diffusion. The paper also provides some thoughts on questions we expect are still unanswered, including mechanisms behind the height dependent mixing phenomenon and the scaling of the experimental results to the significantly greater heights and lower permeability characteristic of the field.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".