Prevention of network destruction of partially hydrolyzed polyacrylamide (HPAM): Effects of salt, temperature, and fumed silica nanoparticles
Why this work is in the frame
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Bibliographic record
Abstract
Polymer flooding is one of the most effective enhanced oil recovery (EOR) methods. High temperature and a high salt content in oil reservoirs significantly decrease the performance of polymer flooding. In this work, the viscoelastic properties of a partially hydrolyzed polyacrylamide (HPAM) solution with and without salt (NaCl) and at two different temperatures (35 °C and 70 °C) were evaluated using rheological approaches. Two fumed silica nanoparticles (NPs) featuring different surface chemistries were used, and their ability to prevent destruction of the polymer network structure against salt addition and temperature increase was investigated. Linear rheological tests (frequency sweep, creep, and creep recovery) and nonlinear rheological tests (large amplitude oscillatory shear) were employed to evaluate the network structure of these systems. The results showed that either adding salt or increasing the temperature destroyed the mechanical integrity of the HPAM 3-dimensional elastic network. However, the introduction of both types of NPs at a sufficient concentration maintained the network structure of HPAM solutions in the small deformation region. In the large deformation region, it was shown that the extent of intra-cycle shear-thickening behavior in the HPAM solution (T = 35 °C and without any salt) decreased by incorporating salt or by increasing the temperature. Moreover, upon incorporating either of the NPs to the HPAM solution, the nonlinear viscoelastic behavior dramatically changed, and the critical strain (linear to nonlinear transition) decreased to a much lower strain amplitude. The outcomes of this study will help petroleum scientists to design more efficient EOR methods.
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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 it