Flow characteristics of three enhanced oil recovery polymers in porous media
Bibliographic record
Abstract
ABSTRACT This article presents an experimental study aiming to explore the relationship among rheological properties, flow characteristics in porous media, and enhanced oil recovery (EOR) performance of three typical EOR polymers. The results suggest that xanthan gum exhibits a very pronounced shear‐thinning behavior, which is probably also the reason explaining its moderate adsorption extent within porous media (thickness of adsorbed layer, e = 3.1 μm). The advanced viscoelastic properties coupled with the less adsorption extent compared to the hydrophobically modified copolymer (HMSPAM) allow xanthan gum to establish a “piston‐like” displacement pattern and lead up to 49.4% original oil in place (OOIP) of the cumulative oil recovery during polymer flooding. Regarding HMSPAM, the significant permeability reduction of the porous media induced by multilayer adsorption (e = 5.6 μm) results in much higher drive forces (ΔP) in the extended waterflooding stage, which further raises the cumulative oil recovery by 18.5% OOIP. In general, xanthan gum and HMSPAM totally produced 84% OOIP which is 15% higher than the extensively used EOR polymer, hydrolyzed polyacrylamide (HPAM), under the same experimental conditions. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015, 132, 41598.
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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".