Quantification of<i>Sor</i>Reduction during Polymer Flooding Using Extensional Capillary Number
Bibliographic record
Abstract
Summary Since the introduction of viscous/capillary concepts by Moore and Slobod (1956), several modifications and advancements have been made to the capillary number (Nc) so that it could have a better correlation with residual oil saturation (Sor) during enhanced oil recovery (EOR). In subsequent years, laboratory-scale studies have indicated that the viscoelastic polymers can influence the Sor reduction at relatively higher fluxes and Nc. Although the flux rate of at least 1 ft/D is reported to be needed for viscoelastic polymers to reduce Sor to a noticeable extent, significant Sor reductions were reported to occur only at higher fluxes that are likely to be seen in the reservoir closer to the wellbore. At similar levels of flux and Nc, the polymer solutions with significant elastic properties have shown higher Sor reduction than viscous polymer of similar shear rheology. However, the existing models used for correlating the polymer’s viscoelastic effect on Sor reduction relies on either core-scale Nc and/or the oscillatory Deborah number (De). De also has limitations in quantifying the polymer’s viscoelastic effects at different salinities. In this paper, a modified capillary number called an extensional capillary number (Nce) is developed using the localized pore-scale extensional viscosity. For viscoelastic polymer solutions, pore-scale apparent viscosity dominated by localized extensional viscosity is calculated to be significantly higher than core-scale apparent viscosity. We provide rheological insights using the variable-strain-rate concept to explain why and when the pore-scale apparent viscosity could become significantly higher, even at a flux of approximately 1 to 4 ft/D, and why it will not be reflected on the core-scale apparent viscosity or pressure drop. An exponential correlation was developed between Nce and Sor using the extensive coreflood experimental data sets extracted from various literature. Performance of Nce for predicting the viscoelastic polymer’s residual oil recovery is compared with conventional Nc, De, and a recent correlation. The results show that newly developed Nce can predict the Sor during polymer flooding for a wide range of operational and petrophysical conditions, including brine-salinity effects.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".