Investigation of Diffusion Coefficients of Heavy Oil and Hydrocarbon Solvent Systems in Porous Media
Bibliographic record
Abstract
Abstract Solvents can be injected to dilute viscous heavy oil or bitumen and improve the recovery of the vast reserves of heavy oil and bitumen in Canada. In an evolution of the SAGD and VAPEX processes, some new schemes that use solvent and steam appeared to offer a more economical and environmentally sound alternative to extract heavy oil and bitumen compared to SAGD alone. Mass transfer rates determine whether these solvent-assisted processes are feasible for heavy oil and bitumen recovery. The solvent-bitumen diffusion coefficient is a basic parameter needed. According to previous literature, the effective diffusion coefficient in porous media is much smaller than the true diffusion coefficient in bulk fluids. However, good-quality data from diffusion experiments of heavy oil and hydrocarbon solvent systems for effective diffusion coefficients determination in porous media is still scarce. This paper presents diffusion experiments of liquid solvent in heavy oil saturated sand using X-ray Computer Assisted Tomography (CAT), and determines the effective diffusion coefficients based on an updated approach, which considers porosity variation of porous media and volume changes on mixing. In addition, the relationship between the effective diffusion coefficient of solvent in oil saturated sand pack and the true diffusion coefficient in bulk fluids is investigated.
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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".