An Experimental Study of Steam-Solvent Coinjection for Bitumen Recovery Using a Large-Scale Physical Model
Bibliographic record
Abstract
Summary In this paper, we present a solvent-assisted steam-assisted gravity drainage (SA-SAGD) experiment with multicomponent solvent (i.e., condensate) using a large physical model. The sandpack for the experiment had a porosity of 0.33 and a permeability of 5.6 darcies in the cylindrical pressure vessel that was 1.22 m in length and 0.425 m in internal diameter. The sandpack was initially saturated with 93% Athabasca bitumen and 7% deionized water. The main objective of this research was to study the in-situ thermal/compositional flow and produced bitumen properties in SA-SAGD with condensate. After the preheating of the sandpack for 24 hours, SA-SAGD with 2.8-mol% condensate was performed at 50 cm3/min (cold-water equivalent) at 3500 kPa for 3 days. The experimental data of production, injection, and temperature distribution were recorded. Also, 10 samples of produced oil were taken and analyzed for density and asphaltene content. The sandpack was excavated after the experiment to analyze the asphaltene content in the remaining oil at different locations. A numerical simulation model was calibrated based on the data of material balance and temperature distribution, and it was validated with properties of the produced and excavated samples. The simulation model used fluid models based on experimental data of viscosities, densities, and bubblepoints for four condensate/bitumen mixtures. Results showed that SA-SAGD was efficient in bitumen recovery with a cumulative steam-to-oil ratio (SOR) that was two to three times smaller than that in SAGD using the same physical model. Detailed analysis of the calibrated simulation model indicated that SA-SAGD enabled the steam chamber to expand more efficiently with a smaller amount of water throughput than SAGD. Volatile solvent components tended to remain in the chamber, and the condensed solvent components acted as a miscible carrier for bitumen components. The analysis further showed that the more efficient oil recovery in SA-SAGD occurred with predominantly cocurrent flow of oil and water near the chamber edge. SA-SAGD recovered a larger amount of asphaltene components (i.e., less in-situ upgrading) than SAGD likely because of its lower chamber temperature, shorter production period, and enhanced local displacement efficiency.
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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 | 0.000 | 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) | 0.001 | 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".