Enhanced polymer flooding using a novel nano‐scale smart polymer: Experimental investigation
Bibliographic record
Abstract
Abstract Polymer flooding is a well‐known commercial method among enhanced oil recovery (EOR) methods. Despite its successful development, this method could still be improved considerably by utilizing new polymeric materials and systems. The main objective of this study is the implementation of smart‐covered polymer particles (SCPP) prepared by multistep inverse emulsion polymerization, to improve polymer flooding efficiency. Successive to the average molecular weight determination of the core polymer using the dilute solution method, the dissolution behaviour of SCPPs is examined at reservoir temperature in a specific setup. In addition to investigating the efficiency of SCPP flooding, polymer flooding experiments in a micromodel setup are examined. The flooding efficiency of conventional polyacrylamide and the newly developed SCPP solutions are compared with the water flooding process. Our results provide new insight into the ability of coated polymers to enhance the recovery efficiency of polymer flooding processes.
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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 | 0.000 | 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 | 0.001 | 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".