Solvent Injection Strategy for Low-Temperature Production from Fractured Viscous Oil Reservoirs
Bibliographic record
Abstract
Viscous oil resources have great potential to help meet the future demand for petroleum products as conventional resources are depleted. Currently high temperature steam injection is the recovery process of choice, with high energy intensity and associated greenhouse gas emissions. The work presented here explores a low-temperature solvent-only injection strategy targeting fractured systems. The warm solvent is in the vapor phase when injected into the reservoir but will condense when it contacts the cold oil and reservoir rock (liquid extraction). After the system has reached the target operating temperature, the injected solvent remains in the vapor phase when it contacts the oil (solvent-enhanced gravity drainage). The experiments discussed in this work explore the key parameters (permeability, temperature/pressure, in situ injection rate, and solvent type) that influence each production mechanism. The primary impact of decreasing permeability is a proportional decrease in film gravity drainage rate. A decrease in temperature slows the mass transfer during the liquid extraction phase and decreases the drainage rate during the film gravity drainage phase. Increasing the in situ injection rate leads to improved liquid extraction because of higher concentration gradient in the solvent-rich liquid phase at the oil/solvent interface. Solvent type affects both mechanisms and changes the nature and amount of asphaltene precipitation. Pentane yields relatively less asphaltene precipitate than butane (18 wt % vs 11 wt % asphaltene content in residual oil). Residual oil saturation was observed to increase as permeability and/or temperature were decreased.
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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".