Synthetic copolymer (AM/AMPS/DMDAAC/SSS) as rheology modifier and fluid loss additive at HTHP for water‐based drilling fluids
Bibliographic record
Abstract
ABSTRACT In the petroleum industry, high temperature and high pressure (HTHP) would dramatically worsen rheological properties and increase fluid loss volumes of drilling fluids. Synthetic polymer as an indispensable additive has attracted more and more attention recently. In this article, a new copolymer (named AADS) of 2‐acrylamide‐2‐methylpropanesulfonic acid, acrylamide, dimethyl diallyl ammonium chloride, and sodium styrene sulfonate was synthesized through aqueous solution polymerization. The chemical structure of the copolymer was characterized by Fourier transform infrared spectroscopy and nuclear magnetic resonance. Moreover, its thermal stability was simultaneously analyzed using a differential scanning calorimetry. The results showed that the synthetic polymer contained all the designed functional groups, and its structure was consistent to the desired one. Under contamination of sodium chloride, AADS solution maintained relatively high viscosity in high concentration brine, showing a good antisalt capacity. Furthermore, the effect of AADS content and temperature on rheological behavior and fluid loss volume of the water‐based drilling fluid (WBDF) containing the synthesized product were investigated according to the American Petroleum Institute standard. Results showed that the rheological and filtration properties of the prepared WBDF were improved with the increase in the AADS concentration before and after the thermal aging test. In addition, in the temperature range of 80–240 °C, a reversible rheological behavior was observed during the heating–cooling process, and the HTHP fluid loss was controlled within 22.5 mL, suggesting that the copolymer AADS was suitable for making WBDF s with high temperature resistance. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136 , 47813.
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 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 | 0.000 |
| 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".