Experimental Investigation of the Effect of Solvent Type and Drainage Height on the Performance of Vapor Extraction (VAPEX) Process in Heavy Oil Systems
Bibliographic record
Abstract
Abstract Available large resources of heavy oil and bitumen in Western Canada are potential future energy sources. Hence, looking for an economically viable, technically feasible, and environmentally friendly heavy oil recovery technique is inevitable. Although the dramatic decrease in the viscosity of heavy oil with the temperature increase makes the thermal recovery techniques the first choice for these reservoirs, cost associated with generating the required heat, excessive heat loss to the surrounding formations, and large amount of CO2 emitted during these thermal processes are some of major economical and environmental concerns. Solvent-based heavy oil recovery methods have recently gained some attention due to the potential advantages over the thermal processes. It has been found that the viscosity reduction resulted from injecting the appropriate solvent is comparable to that obtained by heating in some cases. In this paper, the vapor extraction (VAPEX) process is experimentally investigated to examine the effect of injecting different solvents and drainage heights on the heavy oil recovery. For this purpose, two large visual rectangular sand-packed VAPEX models with the heights of 24.5 cm and 47.5 cm and permeability of about 5 ~ 7D were employed. A heavy oil sample with viscosity of 2500 ~ 5500 cP was used to saturate both models. Pure propane, methane, and carbon dioxide where considered as respective solvents and injected in both models under the same operating conditions. The heavy oil production rate and the produced gas-oil ratio where measured periodically during the course of experiments. In addition, the asphaltene content and the visual observation of the gas chamber evolution were monitored. It was found that the drainage height has a significant impact on the production rate and the ultimate heavy oil recovery. The experiments with smaller drainage height showed higher recovery factor and faster recovery process for similar period of injection-production. Among three different solvents utilized in this study, propane with lower vapor pressure and higher solubility showed more promising results. Additionally, CO2 and methane were used as carrier gases and a series of CO2-based VAPEX process were conducted. Results indicated that CO2-based VAPEX could be used as a means of feasible heavy oil recovery.
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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".