Alteration of matrix wettability during alternate injection of hot-water/solvent into heavy-oil containing fractured reservoirs
Bibliographic record
Abstract
Abstract An alternate injection of solvent and hot water/steam called Steam-Over-Solvent injection in Facture Reservoirs (SOS-FR) has been recently suggested and tested by our research group. In this process, most oil is produced during the solvent phase and then hot water/steam phase is assigned, mainly to retrieve the solvent. Oil recovery during this phase is typically low due to limited thermal expansion in the case of oil-wet matrix, and because capillary imbibition and gravity drainage driven by viscosity reduction do not have a significant contribution to the recovery. Wettability alteration toward more water-wet state will, however, enhance these mechanisms. Based on these facts, different wettability alteration agents were tested including cationic and anionic surfactants, ionic liquids, nano-fluids, high pH solutions, and low salinity water. The potential of these materials to modify the wettability of aged sandstone and limestone samples was evaluated using imbibition tests. Berea sandstone (aged to be oil-wet) and Indiana limestone samples were saturated with heavy oil (3, 600 cp). After the wettability modification was confirmed using different tests, the SOS-FR method was applied. The process was initiated by soaking cores into solvent (heptane or diluent oil) and the oil recovery was estimated using refractive index measurements. Then, two different experimental schemes were followed. In this first scheme, different brines were used and the oil production readings were taken periodically. These experiments will yield additional oil recovery (and solvent retrieval) by capillary imbibition and enhance gravity drainage if the wettability alteration due to solvent effect in the previous phase and chemical injected in the subsequent phase was achieved. In the second scheme, the heptane was retrieved first by hot-water exposure and the capillary imbibition tests were performed to test the selected chemical additive solutions as the wettability alteration agents. After conducting a total of 28 experiments, the most promising wettability alteration agents were marked and optimal application conditions (i.e., temperatures, injection sequence) were identified.
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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".