Effect of Elasticity During Viscoelastic Polymer Flooding: A Possible Mechanism of Increasing the Sweep Efficiency
Bibliographic record
Abstract
Abstract It has been long believed that the viscoelasticity of polymer solution improves the displacement efficiency in polymer flood operations, but the individual effect of elasticity has not been distilled for a single viscoelastic polymer. In this study, the effect of elasticity of polymer-based fluids on the sweep efficiency is investigated by injecting two polymer solutions with similar shear viscosity but significantly different elastic characteristics. Blends of various grades of polyethylene oxide (PEO) with similar average molecular weight and different molecular weight distribution (MWD) were prepared by dissolving in deionized water. The polymer solutions exhibited identical shear viscosity but different elasticity. A series of experiments were performed by injecting the polymer solutions in a special core holder designed to simulate radial flow through a sandpack, which was saturated with mineral oil. Injection was done through a perforated injection line located at the center of the cell and fluids were produced through two production lines located at the periphery. The experiments were conducted within a shear rate range of field applications. Since both polymer solutions had similar viscosity behavior but different elastic properties, it was possible to see the effect of elasticity on the displacement efficiency alone. Results of the polymer flooding experiments indicated that the sweep efficiency of a polymeric fluid could be effectively improved by adjusting the MWD of polymer solution at constant shear viscosity and concentration of the polymer. The polymer solution with higher elasticity exhibited considerably higher resistance to flow through porous media than the solution with lower elasticity resulting into higher displacement efficiency and lower residual oil saturation.
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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 | 0.001 | 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".