摘要
针对塔河油田12区超稠油的性质,进行了超稠油掺苯乙烯焦油降黏实验及黏度预测模型的研究。采用苯乙烯焦油和柴油对超稠油进行不同掺稀比的降黏实验,用非线性宾汉模型进行流变数据拟合,并将实验测得的混合油黏度与预测模型进行匹配。结果表明:超稠油掺混20%苯乙烯焦油的降黏效果与超稠油掺混10%柴油的降黏效果相同,降黏率大于97%,掺稀比越大、温度越高,混合油黏度越低。混合油的流变模型符合非线性宾汉模型,呈现出一定的剪切稀释性。当超稠油与苯乙烯焦油的黏度比低于1.76×104时,混合油黏度可采用Cragoe修正模型和双对数修正模型Ⅱ进行计算,双对数修正模型Ⅱ对苯乙烯焦油与超稠油混合油的黏度预测效果最好,平均相对偏差为9.4%。
According to the properties of super heavy oil in block 12 of Tahe Oilfield,the experiment and viscosity prediction model of blending styrene tar to reduce super heavy oil viscosity were studied.In the case of different blending ratios,the experiments to reduce super heavy oil viscosity was carried by using styrene tar and diesel oil.The rheological data was fitted by the nonlinear Bingham model,and the viscosity data of blended oil measured by the experiment was matched with the prediction model.The results show that the visbreaking effect of 20%styrene tar blended with super heavy oil was the same as that of 10%diesel blended with super heavy oil,and the rate of viscosity reduction was greater than 97%.The higher the blending ratio and the temperature,the lower the viscosity of blended oil.The rheological model of blended oil conforms to the nonlinear Bingham model.The blended oil shows the shear thinning phenomenon.When the viscosity ratio of super heavy oil to styrene tar is less than 1.76×104,the viscosity of blended oil can be calculated by Cragoe Modified model and Double Logarithmic Modified modelⅡ.Double Logarithmic Modified modelⅡhas the best viscosity prediction effect on blended oil of styrene tar and super heavy oil,which the mean relative deviation is 9.4%.
作者
裴海华
刘冬鑫
张贵才
单景玲
蒋平
PEI Haihua;LIU Dongxin;ZHANG Guicai;SHAN Jingling;JIANG Ping(College of Petroleum Engineering in China University of Petroleum,Qingdao 266580,Shandong,China)
出处
《化工进展》
EI
CAS
CSCD
北大核心
2020年第S02期135-141,共7页
Chemical Industry and Engineering Progress
基金
国家重点研发计划(2018YFA0702400)
山东省自然科学基金(ZR2019MEE085)
中央高校基本科研业务费专项资金(18CX02096A)。
关键词
超稠油
掺稀降黏
苯乙烯焦油
流变性
黏度预测模型
super heavy oil
blending light oil for viscosity reduction
styrene tar
rheological property
prediction model of viscosity