Investigation of performance of dual crosslinked hydrogel by modified Zener model in high temperature reservoirs
Bibliographic record
Abstract
This paper aims to study the impact of AMPS on the structure and viscoelastic behavior of hydrogels. A copolymer of acrylamide and 2-acrylamido-2-methylpropane sulfonic acid (AMPSA), N,N-methylene bisacrylamide (MBA), and aluminum persulfate (APS) were synthesized using free radical polymerization. The percentages of AMPSA were 10, 30, 50, and 70%. Polyethyleneimine (PEI), was added as a second crosslinker. The hydrogel’s equilibrium swelling behavior and microscopic structure were examined through SEM and ESEM tests. Rheology, TGA, DSC, and coreflooding experiments were also conducted to scrutinize the hydrogel’s performance under stress and strain, thermal stability, and efficacy in reducing water permeability and managing water, respectively. The optimal sample exhibited an equilibrium swelling of 22 and maintained structural strength in its swollen and pressurized states, confirming the existence of a porous structure and associated cages. The Zener model corroborated the solid-like behavior of hydrogel, while the sweep frequency test revealed the hydrogel’s three-dimensional structure, elastic state, and strength. The hydrogel showed an impressive capacity to retain its elastic structure even when subjected to 1%, 100%, and 1000% strains. TGA and DSC tests attested to the optimal thermal stability of the hydrogel, ensuring performance at temperatures exceeding 120 °C. Finally, coreflooding test results demonstrated a significant reduction in water permeability from 0.112 to 0.005 D before and after injecting the optimal hydrogel, resulting in an almost 70% decrease in water cut. Consequently, the dual-crosslinked hydrogel with a ratio of 7:3, AM/AMPSA, emerged as the most promising candidate for hydrogel injection in sandstone reservoirs at high temperatures.
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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 | 0.001 |
| 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".