Effect of Degree of Branching on the Mechanism of Hyperbranched Polymer To Establish the Residual Resistance Factor in High-Permeability Porous Media
Bibliographic record
Abstract
To improve a polymer’s oil recovery power, it is imperative to discuss its residual resistance factor (RRF), which is a significant parameter in the field and is associated with the polymer molecular structure. This study investigated the capability of three kinds of hyperbranched polymers (HPDAs) with various degrees of branching to establish the RRF in high permeability porous media by way of a one-dimensional sandpack model under different polymer solution concentrations, permeabilities, and injection rates. In addition, the mechanisms of these polymers to establish the RRF were surveyed through altering the wettability of the rock surface. Furthermore, the diameter distribution and microstructure of the injected and produced polymer solution were determined by utilizing dynamic light scattering and scanning electron microscopy, respectively. The experimental results showed that the RRFs of three kinds of hyperbranched polymers were different in variation trend with changes in external conditions. As the degree of branching increased, the dominant mechanism of the polymer to establish retention and the RRF gradually shifted from surface adsorption to mechanical trapping. And the larger the proportion of the mechanical trapping effect was, the stronger the ability to build the RRF became. This was mainly because that the higher the degree of branching of the polymer is, the higher the branched chain number is, the larger the hydrodynamic radius of polymer solution becomes, the stronger the structure formed between end branches becomes, and the lesser the damage caused to the polymer by high permeability medium is.
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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 | 0.001 |
| 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".