Bibliographic record
Abstract
Canada has about one-third of the world's known petroleum reserves in the form of heavy oil and bitumen, which can meet our energy needs for the next two centuries. In this context, the vapor extraction (Vapex) of heavy oil and bitumen has drawn considerable attention in recent years. Not only this process has the potential to sequester greehouse gases besides requireing low energy costs and capital investment, but also the capability of in situ upgrading of heavy oil. At present, there is a significant interest in the determination of the dispersion of solvent gases during Valex in order to predict the amount and time scale of oil recovery as well to optimize the field operations. Not much research has been done so far to investigate dispersion in presence of fluid flow that is transverse to gravity such as in Vapex. In this work, the dispersion of butane solvent gas is determined as a linear function of its concentration in heavy oil and bitumen based on Vapex experiments carried out in the Transport Modeling Laboratory at Ryerson University. A cylindrical wire mesh, which had a cavity of 21 cm high and 6 cm diameter, packed with homogenous porous media satursated with Athabasca heavy oil was used as a physical model for heavy oil vapor interface. The physical model was packed with three different sizes of glass beads. The permeanbilites of the different homogenous glass beads packing were tested. For each model, an experiment was conducted at a room temperature with ± 0.5oC variation, and pressure close to butane dew point with variation ± 0.007 MPa. Under these conditions, the physical model was expose to a butane solvent gas, which diffuses into physical model, and gets absorbed in Athabasca bitumen. As a result of the gas absorption, a significant reduction in viscosity was experienced. The diluted live oil was drained along the solvent vapro/oil interface under the action of gravity. The decrease in mass of the physical model was measured and recorded every 1 minute. Average live oil viscosity, average density, and average dissolved butane mass fraction in Athabasca bitumen sample were determined to be 2.742 cP, 0.86 g/cm3, and 0.48 respectively. These experiments were simulated by a mathematical model, which was used to determined the dispersion coefficient of butane gas into Athabasca bitumen. The dispersion coefficient of butane gas was considered as a linear function of its concentration in the porous media. The mathematical model was numerically solved using finite difference method. Different values for dispersion coefficient and butane saturation mass fraction were used in the simulation. Steepest decent method was used to iteratively evaluate dispersion coefficient and minimize the error. The optimum values of dispersion coefficient and butane gas saturation solubility in Athabasca bitumen were determined by matching the calculated and experiemental values of live oil production.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".