Effect of Dead-Oil Viscosity and Injected-Solvent Type on SVX Process Performance
Bibliographic record
Abstract
Summary This work presents experimental results of four 3D-physical-model experiments that were performed to evaluate the dependence of the solvent-vapour-extraction (SVX) recovery process performance on initial dead-oil viscosity and injected-solvent-mixture composition. 0 Model excavation studies were also performed to approximate the solvent movement in the physical model and to map out the residual oil saturation and precipitated asphaltenes. The field-scale application and optimization of SVX processes requires that relationships be established among oil-production rates, solvent usage, and important process parameters (e.g., matrix permeability, initial dead-oil viscosity, solvent-mixture composition, and solvent usage). This work has attempted to generate such relationships for the two most promising mixed-solvent systems being considered for use in heavy-oil reservoirs. The analysis of the experimental results revealed that the initial dead-oil viscosity had a significant effect on the SVX performance. Higher oil-production rates were achieved with the lower-viscosity oils for both injected-solvent-mixture types, with a more-pronounced effect observed when using the CO2/C3 solvent mixture. The results also showed that the CO2/C3 mixture resulted in earlier solvent breakthrough and initial oil production, reduced solvent-makeup requirements (i.e., better solvent recycle stream), and reduced solvent retention in the model/reservoir, as compared with the C1/C3 solvent mixture. The residual-oil-saturation mapping showed that the CO2/C3 mixture led to comparatively lower values in the drained regions and a higher amount of precipitated asphaltenes remaining in the model, although there was evidence of some precipitated asphaltenes close to both the injection and production wells in all four experiments, regardless of the solvent-mixture type. Finally, this mapping also indicated that the solvent/oil interfaces and solvent chambers were more uniform and predictable for the CO2/C3 solvent-mixture injection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".