A Study of the Impact of Permeability Barriers on Steam-Solvent Coinjection Using a Large-Scale Physical Model
Bibliographic record
Abstract
Abstract This paper presents a solvent-assisted steam-assisted gravity drainage (SA-SAGD) experiment using condensate in a large physical model. The main objective of this research was to study the impact of permeability barriers on the in-situ thermal/compositional flow and the produced bitumen properties in SA-SAGD using condensate. A pressure vessel of 0.425 m in diameter and 1.2 m in length contained unconsolidated sands and two horizontal shale plates as permeability barriers. The two shale plates were placed at different elevations above the injection well and horizontally staggered so that they could make the main hydraulic paths tortuous during the experiment. The sandpack had a porosity of 0.34 and a permeability of 5.6 D, and it was initially saturated with 95% Athabasca bitumen and 5% deionized water. After 24 hours of preheating, SA-SAGD with 2.8 mol% condensate was performed at 35 cm3/min (cold-water equivalent) at 3500 kPa for 4 days. The production, injection, and temperature distribution were recorded. Produced oil samples were analyzed for density and asphaltene content. The sandpack was excavated after the experiment to analyze the oil saturation and asphaltene content in the remaining oil at different locations. Results were compared with the previous SAGD and SA-SAGD experiments using the same physical model with a homogeneous sandpack. Results showed that SA-SAGD was efficient in the presence of permeability barriers with a cumulative steam-to-oil ratio (SOR) that was two to three times smaller than that ofthe homogeneous SAGD case. Temperature data indicated that a steam chamber vertically expanded from the lower part to the upper part through tortuouspaths of lower temperatures.The emerging steam chamber above the shale plates occurred by convective heat from the injection well through lower-temperature hydraulic paths between shale plates. This should have involved light to intermediate solvent components that enabled the steam chamber to expand away from the injection well. This highlights the important role of volatile solvent components in the growth of a steam chamber in SA-SAGD under heterogeneity. The produced bitumen density in this research was closer to the original bitumen than in the homogeneous SA-SAGD case because the bitumen dilution and the solvent retention increased by the tortuous flow regime resulted in efficient drainage of oil at lower temperature.
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 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 | 0.001 |
| 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".