Preparation of water self‐dispersible nano‐ <scp> CaCO <sub>3</sub> </scp> and its enhancement of P( <scp>AM</scp> ‐ <scp>SA</scp> ‐ <scp>MO8</scp> ) gel for profile control
Bibliographic record
Abstract
Abstract In this paper, a novel water self‐dispersible nano‐CaCO 3 was obtained by surface modification method using the betaine surfactant as the modifier and its potential to enhance the performance of polymer gels for enhancing oil recovery was investigated. The synthesis conditions of nano‐CaCO 3 and the formulation of polymer gel profile control system were optimized. Based on the experimental results, the recommended synthesis conditions for nano‐CaCO 3 are as follows: calcium oxide slurry concentration of 5%, laurylamine propyl betaine (LAB) dosage of 0.6 wt.% to calcium oxide, carbonation temperature of 10°C, using a 0.5 μm aeration head and a gas flow rate of 0.1 L/min. The product is referred to as LAB‐CaCO 3 . The optimal formulation of polymer gel profile control system is 1500 mg/L LAB‐CaCO 3 , 5000 mg/L polymer, and 3500 mg/L crosslinker. This system can achieve a blocking efficiency of 98.51% and an enhanced oil recovery rate of 35.4%, demonstrating long‐term stability and excellent profile control performance. The findings of this study provide valuable insights for the development of polymer gel profile control in oilfield.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".