Enhancing Oil Rate in Solvent Vapour Extraction Processes through Tee-Well Pattern
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Bibliographic record
Abstract
Abstract The production flow rate in classical VAPEX is far too low for the process to be considered commercially viable. This is largely because the classical process utilizes forces of buoyancy to distribute the solvent and gravity to drain the diluted oil to the producer. This paper presents a new well pattern that may enhance the oil flow rate two to ten times over the classical approach. In the new well pattern, additional horizontal injectors, perpendicular to the injector and the producer in classical VAPEX, are placed in the top-most region of the reservoir. The enhanced oil rate mechanism for this new well pattern involves two features. First, the injection pressure of the top injectors is set slightly higher than the bottom injector pressure. This facilitates a downward driving force to assist gravity drainage of diluted oil to the producer. Second, the supplementary injectors generate an additional diluted oil profile perpendicular to the diluted oil profile of the classical VAPEX process. Therefore, in the new well pattern, the heavy oil is solvent contacted and diluted in both ik and jk planes, whereas in classical VAPEX, the heavy oil is diluted in only one. A series of numerical simulations were conducted to evaluate this process. In order to obtain reliable evaluation results, the numerical dispersion was eliminated through extrapolating the simulation results at different grid sizes to an infinitesimal grid size (Δy→0). The simulation results suggest that the oil flow rate can be enhanced two to ten times greater than with classical VAPEX, depending on the well spacing of the top injectors. For example, for a well spacing of the top horizontal injectors of 120 m, the oil flow rate from the original producers will be 5.5 times higher than in the VAPEX scenario. The paper also discusses the effects of the design factors and formation/fluid uncertainties on the performance of this process. Finally, thinner reservoirs and reservoirs with a gas cap are discussed.
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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 | 0.001 |
| 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 it