Mechanics of Heavy-Oil and Bitumen Recovery by Hot Solvent Injection
Bibliographic record
Abstract
Summary In earlier work (Pathak et al. 2010, 2011), we presented the initial results for heavy-oil and bitumen recovery using heated solvent vapors. The heavy-oil- and bitumen-saturated sandpack samples of different heights were exposed to heated vapors of butane or propane at a constant temperature and pressure for an extended duration of time. The produced oil was analyzed for recovery, asphaltene content, viscosity, composition, and refractive index. Recovery was found to be very sensitive to temperature and pressure. The current work was undertaken to better understand the physics of the process and to explain the observations of the earlier experiments using additional experiments on tighter samples of different sizes, numerical simulation, and visualization experiments. The effects of temperature and pressure on the recovery were studied using a commercial reservoir simulator. Propane and butane were used as solvents. Asphaltene precipitation was also modeled. A qualitative history match with the experiments on different porous-media types was achieved by mainly considering the permeability reduction caused by asphaltene precipitation; pore plugging; the extent of interaction between the solvent and oil phases; and parameters such as model height, vertical permeability, and gravity. The effect of asphaltene deposition on models of varying permeabilities was also studied. To investigate the phenomenon further, visualization experiments were performed. 2D Hele-Shaw models of different dimensions were constructed by joining two Plexiglass sheets from three sides, or in some experiments, from all sides. The models were saturated with heavy oil and left open on one side (or all sides) and were exposed to different types of solvents. The setup was monitored continuously to observe fluid fronts and asphaltene precipitation. By use of this analysis, the mechanics of the process was clarified from the effect of solvent type on the recovery process. The optimum operating temperature for the hot-solvent process and the dominant mechanisms were identified. The dynamics of the asphaltene deposition and its effect on oil recovery were clarified through visual and numerical models.
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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".