Retrieval of Solvent Injected During Heavy-Oil Recovery from Water - and Oil-Wet Reservoirs: Pore Scale Analysis at Variable Temperature Conditions
Bibliographic record
Abstract
Abstract Solvent injection has been given attention to enhance oil recovery by sole use or in combination with a thermal method to develop light, medium, and heavy-oil fields. To make this process efficient, retrieval of expensive solvent efficiently is required. This can be achieved by alternative injection of water (WAG) if the reservoir is homogeneous. In case of heterogeneous reservoirs (fractured carbonates or sands with wormholes), one needs to develop techniques other than viscous displacement to retrieve the solvent diffused into less permeable matrix portion. A method of injecting steam/hot water to heat the solvent to vaporize and retrieve it was introduced recently (steam-over-solvent injection in fractured reservoirs) and tested through core experiments. Although these tests provide valuable data to design the optimal temperature of injected water to make the process viable, the mechanics of the nucleation of the solvent vapor and its entrapment in the pores at the micro scale requires further research. A series of experiments using a 2-D etched glass micromodel (sandstone replica with a fracture) were carried out to investigate the mechanics of solvent retrieval and entrapment at variable temperature conditions. The micromodel was saturated with dyed processed oils and different solvents were injected through fracture. After the solvent was diffused into matrix completely to recover the oil, the model was heated mimicking a thermal method to reach the boiling point of the solvent and retrieve it. The wettability of the micromodel was also altered to achieve water-wet and oil-wet conditions as wettability dictates the phase distribution in the pores. Following the heating phase, water was injected to retrieve the remaining solvent in the liquid or vapor phase. Visual observations of solvent diffusion/dispersion into matrix and its retrieval from the matrix clarified the miscibility process in the presence of an immiscible phase, interaction between different phases in a complex heterogeneous system, and phase distributions as a function of temperature. This information can be used to determine the efficiency of solvent retrieval process and optimal application conditions for EOR applications in heterogeneous sands and carbonates.
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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".