阳离子聚合
盐度
化学工程
水溶液
肺表面活性物质
盐(化学)
流变学
溶解度
粘度
材料科学
复合材料
化学
有机化学
地质学
海洋学
工程类
作者
Jizhen Tian,Jincheng Mao,Wenlong Zhang,Xiaojiang Yang,Chong Lin,Meng Cun
标识
DOI:10.1002/slct.202004274
摘要
Abstract As good thickeners for clean fracturing fluids, high salt‐tolerant surfactants have received increasing attention. Based on previous studies, we have further studied the performances of four surfactants, EDAS (JS‐SO), EHSB (JS‐OH‐SO), ETAC (JN) and EDHB (JS‐OH), in monovalent (NaCl) and divalent (CaCl 2 ) salts. This is of great significance for the application of high‐salinity formation water to directly prepare fracturing fluids. The results showed that in high‐salinity aqueous solutions, both zwitterionic surfactants and cationic surfactants can exhibit extremely strong salt tolerance. The addition of the counter ion salt can destroy the internal salt, thus increasing water solubility of zwitterionic surfactants. Cationic surfactants have strong water solubility, and the counter ion Cl − will weaken the electrostatic shielding effect between the head groups. Surfactants can still maintain excellent network structures under high‐salinity conditions. This is mainly owing to the extreme insensitivity of zwitterionic surfactants to salts and the large initial head group area of cationic surfactants. In actual applications, the formation water from the Tahe Oilfield was used directly to prepare the fracturing fluids. Testing the rheological properties of fracturing fluid systems found that adding a small amount of hydrophobic associating polymers can increase the temperature resistance from 100 °C to 140 °C, and the final viscosity can be maintained above 30 mPa S. At the same time, they all showed excellent proppant suspension properties and extremely low core damage rates. The results indicated that even in high‐salinity formation water and high‐temperature formation, these fracturing fluid systems still have good performances, extremely low damage and meet fracturing fluid industry standards.
科研通智能强力驱动
Strongly Powered by AbleSci AI