Permeability Effects in a Vapour Extraction (VAPEX) Heavy Oil Recovery Process
Bibliographic record
Abstract
Abstract Vapour extraction (VAPEX) process is an effective heavy oil recovery technology because of its significant viscosity reduction through sufficient solvent dissolution and possible asphaltene precipitation. In the past, several researchers have studied the specific effect of permeability on the stabilized heavy oil production rate during a VAPEX heavy oil recovery process. However, physical modeling with relatively low permeabilities close to a typical heavy oil reservoir permeability has not gained enough attention. In this paper, an experimental study is conducted by using a visual rectangular sand-packed high-pressure physical model to examine the detailed effects of permeability ranging from sixteen to several hundred Darcies. More specifically, the heavy oil production rate, solvent-oil ratio, asphaltene content of produced oil, and residual oil saturation are measured. Also, the solvent vapour chamber evolution is visualized. The actual permeability of the sand-packed physical model is measured prior to each VAPEX test and propane is used to extract heavy oil from the sand-packed physical model at P=800 kPa and T=20.8 °C. It is found that, in general, the existing Butler-Mokrys analytical model underestimates the heavy oil production rate if the permeability is high enough and the asphaltene deposition does not plug the porous medium. It is also found that a reduced permeability causes the solvent-oil ratio to increase so that the asphaltene precipitation and deposition may become pronounced. As a consequence, the asphaltene precipitation results in further viscosity reduction of produced oil and an unexpected relatively high oil production rate. The asphaltene content of produced oil is measured to verify the asphaltene deposition phenomenon. Furthermore, the entire VAPEX heavy oil recovery process is visualized to determine the residual oil saturations inside the solvent vapour chamber at different times by using the material balance equation and to study the variations of the so-called solvent vapour chamber rising, spreading and falling phases with the measured permeability of the physical model. Introduction How to effectively and economically recover heavy oil from the tremendous heavy oil and bitumen deposits in Western Canada becomes a key technical issue as the conventional crude oil is being depleted1–3. The extremely high viscosity and almost immobile condition of these deposits under the actual reservoir conditions cause their primary oil recovery to be as low as 6–8% of the original-oil-in-place (OOIP)4, 5. Some thermal-based heavy oil and bitumen recovery processes are currently being applied in oil fields to enhance heavy oil and bitumen recovery, such as steam-assisted gravity drainage (SAGD), cyclic steam stimulation (CSS), and in-situ combustion (ISC)6, 7. Nevertheless, some economic constraints for applying these thermal-based oil recovery processes arise if the high costs of steam generation and excessive heat losses into thin oil reservoirs are considered. In addition, greenhouse gases emission, source water supply and produced water treatment make other enhanced oil recovery techniques more economically viable and environmentally friendly8. The vapour extraction (VAPEX) process is a non-thermal heavy oil recovery process, in which a vaporized solvent is injected from an upper horizontal injection well into a heavy oil reservoir. The solvent-diluted oil is then drained downward by gravity to a lower horizontal production well9, 10. In the past, the VAPEX was experimentally modeled by Butler and Mokrys11 in a vertical Hele-Shaw cell by using two different bitumen
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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 | 0.001 | 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".