Abstract:

The aim of this study is to investigate the effects of modified magnetic nanoparticle mass fraction, solution acidity and alkalinity (pH), oil-water ratio, NaCl concentration, stirring speed and emulsification temperature on the rheological properties of thick oil O/W emulsions, and to reveal the mechanism of their effects in combination with zeta potential, interfacial tension and oil droplet distribution. In order to more deeply and precisely analyze the influence of the above factors on the flow characteristics of emulsion, a six-factor and three-level positive alternating current experiment was carried out, and the power law fluid pressure drop formula was used to calculate the pressure drop per unit pipe length under each group of conditions, and the analysis of variance (ANOVA) and nonlinear regression (NLR) analysis was carried out by applying the SPSS software, and a prediction model of the pressure drop in tubing transport was constructed for the O/W-type emulsions. Finally, the optimal solution for pressure drop was solved using Matlab software. The results show that the oil-water ratio has the most significant effect on the rheological properties of emulsions, and the modified magnetic nanoparticles can successfully prepare thick oil O/W emulsions with an oil-water ratio of 8∶2. When the mass fraction of modified magnetic nanoparticles was controlled at 0.07%, the oil content was maintained at 50.38%, the NaCl concentration was 0.12 mol/L, the stirring speed was set at 664.10 r/min, and the emulsification temperature was maintained at 16.92℃, the tubing pressure drop per unit length of this thick-oil O/W-type emulsion could reach the minimum value, i.e., 66.93 Pa/m, which is an optimal solution. This optimal solution indicates that the lower mass fraction of modified magnetic nanoparticles can realize the thick oil substantial drag reduction transport under low temperature conditions. In addition, the model constructed in this paper shows a good ability to predict the pressure drop under strict orthogonal experimental conditions, which provides a reliable method to evaluate and optimize the conveying performance of thick oil O/W emulsions.

Key words: nanoparticles, polymer, thick oil O/W emulsions, rheological properties, prediction, pressure drop model

摘要：

旨在探讨改性磁性纳米粒子质量分数、溶液酸碱度（pH）、油水比、NaCl浓度、搅拌速度以及乳化温度对稠油O/W型乳状液流变特性的影响规律，并结合Zeta电位、界面张力和油滴分布揭示了其作用机制。为了更深入且精确地分析以上因素对乳状液流动特性的影响，开展了六因素三水平的正交流变实验，采用幂律流体压降公式计算了各组条件下单位管长压降，并应用SPSS软件进行了方差分析和非线性回归分析，构建了一个适用于O/W型乳状液的管输压降预测模型。最后，使用Matlab软件对压降进行了最优解的求解。研究结果显示，油水比对乳状液流变特性影响最为显著，且改性磁性纳米粒子可以成功制备出油水比为8∶2的稠油O/W型乳状液。当改性磁性纳米粒子质量分数控制在0.07%，含油率维持在50.38%，NaCl浓度为0.12 mol/L，搅拌速度设置为664.10 r/min，且乳化温度保持在16.92℃时，该稠油O/W型乳状液的单位长度管输压降能达到最小值，即66.93 Pa/m，该最优方案表明较低质量分数的改性磁性纳米粒子能在低温条件下实现稠油大幅度减阻输送。此外，通过实证研究，所构建的模型在严格的正交实验条件下展现出较好的管输压降预测能力，从而提供了一种可靠的方法来评估和优化稠油O/W型乳状液的输送性能。

关键词: 纳米粒子, 聚合物, 稠油O/W型乳状液, 流变性, 预测, 压降模型