Rheological Assessment of the Elasticity of Polymers for Enhanced Heavy Oil Recovery
Bibliographic record
Abstract
Abstract More recently polymer flooding recovery processes are becoming increasingly attractive due to the improvements in polymer manufacturing, hydration and implementation successes worldwide. This is especially true in the application of polymer for enhancing heavy oil recovery. It has been suggested that the elastic nature of the polymer is equally important to the viscous properties. In the present study, a specialized rheometer was used to determine the viscoelastic properties of both hydrolyzed polyacrylamides (HPAM) and hydrophobically associating polyacrylamides (HAP) used in heavy enhanced oil recovery (EOR) processes. The rheometer has the capability to measure rheological properties in porous capillary plugs providing a more representative picture of non-Newtonian fluid flow in reservoirs. The rheological parameters were determined as influenced by polymer type, concentration, molecular weight, hydrophobicity, salinity and temperature. Increases in elastic tendencies were observed as a function of the first four; however, salinity and temperature were found to have a slightly negative effect. A medium density, hydrophobic polymer showed an earlier onset of elastic contribution at in-depth reservoir shear rates as determined by its Weissenberg number. For heavy oil reservoirs utilizing higher polymer concentrations, the viscoelastic properties of a polymer system should be evaluated in the screening process. Recent studies suggest that viscoelastic polymers can reduce the residual oil saturation below that to waterflood with two different plausible mechanisms at play, depending whether the media is water- or oil-wet. However, in both theories, polymer elasticity is believed to be the dominant force that contributes to the additional reduction in oil saturation. Aside from measuring the elasticity directly, other parameters that quantify a polymer's elastic potential are its relaxation time and Weissenberg number; therefore, the change in these parameters with respect to dynamic shear rate or flow velocity can be further useful for screening purposes.
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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".