Bitumen Recovery from Carbonates by a Modified SOS-FR (Steam-Over-Solvent Injection in Fractured Reservoir) Method Using Wettability Alteration Chemicals
Bibliographic record
Abstract
This study investigates the applicability of the modified version of the previously proposed SOS-FR (steam-over-solvent injection in fractured reservoir) method to recover bitumen from the Grosmont formation in Canada. Three phases were applied on a total of 13 preserved core samples. In Phase 1, the cores taken from three different parts of the Grosmont formation were soaked in a liquid solvent (heptane or distillate) at ambient conditions. The objective of the first phase was to reduce the viscosity of the bitumen in preparation for the second phase which is wettability alteration. In Phase 2, we soaked the samples in water with chemicals. Wettability modifiers tested include high pH solution, cationic surfactants, and ionic liquids because the screening process indicated they are the most useful wettability alteration chemicals for oil-wet carbonates. One of the key benefits of the ionic liquids is that they are environmentally friendly as they are chemically stable with low level of toxicity and flammabiliy. They can also be customized for particular rock/fluid system. On the other hand, pH solutions are economically attractive, in comparison with other wettability modifiers. Finally, Phase 3 was applied by increasing temperature to the bubble point of the solvent to mimic hot-water injection with chemicals. Each phase was analyzed in terms of ultimate oil recovery (and wettability alteration), time to reach this amount, the most suitable wettability alteration chemicals, and soaking times needed. The results revealed that the solvent phase not only affects the bitumen properties, but also changes Grosmont rock characteristics significantly. Wettability alteration of the fractured Grosmont reservoir was observed to be critical for additional oil recovery as well as for solvent retrieval. Specific high pH solution efficiently altered wettability and helped to recover considerable amount of bitumen/solvent mixture fairly quick showing a potential as a low cost chemical to recover bitumen. A discussion about the optimization of the process in terms of the solvent soaking period, wettability alteration chemicals, and the effect of temperature was also included.
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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 | 0.001 | 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".