基于常规物性的石脑油组成预测方法  

PREDICTION OF NAPHTHA COMPOSITION BASED ON CONVENTIONAL PHYSICAL PROPERTIES

作　　者：王佳[1] 焦国凤[1] 周祥[1] 郭锦标[1] 

机构地区：[1]中国石化石油化工科学研究院,北京100083

出　　处：《石油炼制与化工》2014年第12期84-87,共4页Petroleum Processing and Petrochemicals

摘　　要：建立了利用物性数据对石脑油组成进行预测的方法，根据对石脑油样本的整理，选取正构烷烃、异构烷烃、环烷烃和芳烃4个族的54个真实组分来表示石脑油的组成，利用密度、折射率、族组成数据（PIONA值）以及恩式蒸馏曲线等物性数据建立方程组，对该方程组求解得到54个组分的质量分数。选择典型直馏石脑油样品，根据以上方法建立方程组并求解，得到石脑油中各组分的质量分数，并与实测结果进行对比。结果表明，正构烷烃、异构烷烃及环烷烃含量的计算平均误差分别为6．6％，8．5％，5．9％，其中，石脑油中含量较高的C6～C11组分中正构烷烃、异构烷烃和环烷烃含量的计算平均误差分别为3．2％，5．2％，4．4％，说明所建立的模型基本可以反映直馏石脑油的烃类组成分布情况。A method for predicting naphtha composition based on the conventional physical proper﹣ties was established. Based on the data base of RIPP,54 real components were chosen to represent the composition of naphtha,which is divided into 4 groups：n﹣paraffins,iso﹣paraffins,naphthenic and aro﹣matics. A set of simulation equations were built using conventional properties of density,refractive in﹣dex,group composition,and Engler distillation curve of 4 groups to get the mass fractions of 54 compo﹣nents and then compared with the measured results. The results show that the calculated compositions agree well with the measured results. The calculation average error for corresponding normal alkanes, iso﹣alkanes,cyclanes is 6. 6%,8. 5%,5. 9%,respectively. The error of alkanes,iso﹣alkane and cycla﹣nes contents in C6—C11 is 3. 2%,5. 2%,4. 4%,respectively. The above results demonstrate that the established model equations can reflect well the hydrocarbon distribution of straight﹣run naphtha.

关 键 词：石脑油 组成 密度 PIONA值 恩式蒸馏曲线 

分 类 号：TE626.9[石油与天然气工程—油气加工工程]