Extensional Effects during Viscoelastic Polymer Flooding: Understanding Unresolved Challenges
Bibliographic record
Abstract
Summary Several studies have tried to relate polymers’ enhanced oil recovery (EOR) potential to their viscoelastic characteristics such as onset, rheo thickening, extensional viscosity, and Deborah number (De). Contradictions prevail when it comes to reduction in residual oil saturation (Sor) during polymer flooding and the role of extensional properties. De calculated using the oscillatory relaxation time fails to explain the different pressure profiles exhibited by the viscous and viscoelastic polymers. Extensional viscosity has been ignored in many studies as the reason for additional Sor reduction based on the core-scale apparent viscosity and core-scale capillary number (Nc). In recent studies, a significant oil mobilization was shown by the viscoelastic polymers even before the critical Nc, which indicates that the capillary theory breaks out under specific conditions during polymer flooding. Moreover, the additional residual oil recovery caused by the high-salinity polymer solutions cannot be explained by the oscillatory De. In this paper, we compile and examine many such unresolved challenges from various literature with rheological and petrophysical insights. The uniaxial bulk extensional rheology is performed on the relevant polymers using a capillary breakup extensional rheometer to measure the extensional relaxation time, maximum extensional viscosity at the critical De, and strain hardening index. A detailed analysis signifies the role of extensional rheology on the viscoelastic onset, rheo thickening, and Sor reduction even under varying salinity conditions. The results also highlight the advantages of extensional rheology over oscillatory rheology and validate the capillary theory using modified capillary number.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".