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Synthesis and Characterization of Sodium Carboxymethyl Starch‐Graft Acrylamide/1‐Vinyl‐2‐Pyrrolidone Copolymers via Central Composite Design and Using as Filtration Loss Agent in Drilling Muds
Author(s) -
Bai Xiaodong,
Zhang Xuepeng,
Xu Yuqian,
Yong Xuemei
Publication year - 2021
Publication title -
starch ‐ stärke
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.62
H-Index - 82
eISSN - 1521-379X
pISSN - 0038-9056
DOI - 10.1002/star.202000151
Subject(s) - copolymer , grafting , central composite design , acrylamide , response surface methodology , starch , materials science , polymer chemistry , chemical engineering , drilling fluid , monomer , chemistry , nuclear chemistry , composite material , chromatography , polymer , organic chemistry , drilling , engineering , metallurgy
A graft copolymer is synthesized with graft copolymerization of acrylamide (AM) and 1‐vinyl‐2‐pyrrolidone (NVP) grafting onto sodium carboxymethyl starch (CMS) via central composite design (CCD). The initiation system consists of potassium persulfate (KPS) and sodium hydrogen sulfite (SBS). The copolymer is confirmed by infrared spectroscopy, nuclear magnetic resonance hydrogen spectroscopy, scanning electron microscopy, thermogravimetric experiment, and elemental analysis. The rheological performance, filtration loss, cake thickness, and cake fictional coefficient of the drilling mud containing copolymer are evaluated. The results show that copolymers have ability to thicken and reduce filtration volume and have no obvious influence on the thickness and fictional coefficient of the mud cake. Response surface methodology (RSM) is exerted for variable evaluation and optimization. The results indicate that initiator concentration is the main contributing factor to decrease filtration volume and the optimum results are 1.5 wt% (initiator concentration), 1.82 (mole ratio of monomer to starch [AGU]), 66.02 °C (reaction temperature), 3.87 h (reaction time). The predicted value and the actual experimental value are 8.64 and 9 mL respectively with an error of 4.01%. The small error indicates that there is a small deviation between the actual and the predicted values, which also shows that the model is reasonable.