重质油黏度的定量结构-性质关系研究
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摘要
研究了重质油黏度的定量结构-性质关系。将量子化学参数和拓扑指数相结合作为结构描述符,分别用多元线性回归(MLR)和人工神经网络(ANN)建立了结构描述符和黏度之间的校正模型。用留一交叉验证法,验证、评价所建立的MLR和ANN模型的预测能力。对于MLR模型,验证的均方根相对误差为7.77,对于ANN模型,验证的均方根相对误差为7.21,说明建立的MLR和ANN模型都可用于预测重质油的黏度,但ANN模型优于MLR模型。
The quantitative structure property relationship(QSPR) for the viscosity of heavy crude oil was studied.Applied quantum chemical parameters as structural descriptors,the relationship between the quantum chemical parameters and viscosity was modeled with multivariate linear regression(MLR) and artificial neural network(ANN) respectively.Leave one out cross validation(LooCV) was conducted to assess the prediction performance of the developed models.For the MLR model,the root mean square relative error(RMSRE) of Loo-CV was 7.77,for the ANN model,the RMSRE of Loo-CV was 7.21.It was demonstrated that there was a quantitative relationship between the quantum chemical parameters and density.Both MLR and ANN were practicable for modeling this relationship.
The quantitative structure property relationship(QSPR) for the viscosity of heavy crude oil was studied.Applied quantum chemical parameters as structural descriptors,the relationship between the quantum chemical parameters and viscosity was modeled with multivariate linear regression(MLR) and artificial neural network(ANN) respectively.Leave one out cross validation(LooCV) was conducted to assess the prediction performance of the developed models.For the MLR model,the root mean square relative error(RMSRE) of Loo-CV was 7.77,for the ANN model,the RMSRE of Loo-CV was 7.21.It was demonstrated that there was a quantitative relationship between the quantum chemical parameters and density.Both MLR and ANN were practicable for modeling this relationship.
引文
[1]Zhao S,Pu W,Varfolomeev M A,Yuan C,Zhang J,Han X,Wu J.Comprehensive investigations into low temperature oxidation of heavy crude oil[J].Journal of Petroleum Science and Engineering,2018,171:835-842.
[2]蔡耀荣,武瑞明,赵悦,等.重质油沥青质致黏机理研究进展[J].应用化工,2018(5):1033-1037.
[3]Taheri-Shakib J,Shekarifard A,Naderi H.Heavy crude oil upgrading using nanoparticles by applying electromagnetic technique[J].Fuel,2018,232:704-711.
[4]王海梅,吴涛.重质原油管道输送工艺发展现状[J].广东化工,2014,41(10):75.
[5]Alomair O,Jumaa M,Alkoriem A,et al.Heavy oil viscosity and density prediction at normal and elevated temperatures[J].Journal of Petroleum Exploration&Production Technology,2016,6(2):1-11.
[6]张春明,赵红静,肖乾华,李金有.稠油黏度预测新模型[J].长江大学学报(自科版),2005(7):216-218.
[7]窦晓冬,俞春芳,于成峰,郭明,叶长志.二元体系液体混合物黏度的工程应用预测模型[J].化学工业与工程技术,2001,22(6):3-6.
[8]严万洪,王玉洪,汪澜.辽河含水超稠油黏度预测模型[J].辽宁化工,2007(6):366-368.
[9]童刚,陈丽君,冷健,江婷婷.液体黏度模型的建立与实现[J].青岛科技大学学报(自然科学版),2007(6):539-541.
[10]马高红.重质油组分分子结构与黏温性能的关系[D].青岛:中国石油大学(华东),2015.
[11]徐春明,史权.重质油国家重点实验室专刊:重质油化学[J].中国科学:化学,2018,48(4):317-318.
[12]周永昌,蒋涛.用性质关联法估算重油馏分黏度[J].安徽工业大学学报(自然科学版),2006(1):37-40.
[13]梁文杰.重质油化学[M].东营:石油大学出版社,2000.
[14]Wakabayashi T.Viscosity correlation with specific gravity and molecular weight of crude oil fractions[J].Fuel,1997,76(11):1049-1056.
[15]Riazi M R,Al-Otaibi G N.Estimation of viscosity of liquid hydrocarbon systems[J].Fuel,2001,80(1):27-32.
[16]Marrero-Morejón J,Pardillo-Fontdevila E.Estimation of liquid viscosity at ambient temperature of pure organic compounds by using group-interaction contributions[J].Chemical Engineering Journal,2000,79(1):69-72.
[17]周永昌.俄罗斯渣油结构特性及基团贡献法预测沸点的研究[D].北京:中国石油大学,2003.
[2]蔡耀荣,武瑞明,赵悦,等.重质油沥青质致黏机理研究进展[J].应用化工,2018(5):1033-1037.
[3]Taheri-Shakib J,Shekarifard A,Naderi H.Heavy crude oil upgrading using nanoparticles by applying electromagnetic technique[J].Fuel,2018,232:704-711.
[4]王海梅,吴涛.重质原油管道输送工艺发展现状[J].广东化工,2014,41(10):75.
[5]Alomair O,Jumaa M,Alkoriem A,et al.Heavy oil viscosity and density prediction at normal and elevated temperatures[J].Journal of Petroleum Exploration&Production Technology,2016,6(2):1-11.
[6]张春明,赵红静,肖乾华,李金有.稠油黏度预测新模型[J].长江大学学报(自科版),2005(7):216-218.
[7]窦晓冬,俞春芳,于成峰,郭明,叶长志.二元体系液体混合物黏度的工程应用预测模型[J].化学工业与工程技术,2001,22(6):3-6.
[8]严万洪,王玉洪,汪澜.辽河含水超稠油黏度预测模型[J].辽宁化工,2007(6):366-368.
[9]童刚,陈丽君,冷健,江婷婷.液体黏度模型的建立与实现[J].青岛科技大学学报(自然科学版),2007(6):539-541.
[10]马高红.重质油组分分子结构与黏温性能的关系[D].青岛:中国石油大学(华东),2015.
[11]徐春明,史权.重质油国家重点实验室专刊:重质油化学[J].中国科学:化学,2018,48(4):317-318.
[12]周永昌,蒋涛.用性质关联法估算重油馏分黏度[J].安徽工业大学学报(自然科学版),2006(1):37-40.
[13]梁文杰.重质油化学[M].东营:石油大学出版社,2000.
[14]Wakabayashi T.Viscosity correlation with specific gravity and molecular weight of crude oil fractions[J].Fuel,1997,76(11):1049-1056.
[15]Riazi M R,Al-Otaibi G N.Estimation of viscosity of liquid hydrocarbon systems[J].Fuel,2001,80(1):27-32.
[16]Marrero-Morejón J,Pardillo-Fontdevila E.Estimation of liquid viscosity at ambient temperature of pure organic compounds by using group-interaction contributions[J].Chemical Engineering Journal,2000,79(1):69-72.
[17]周永昌.俄罗斯渣油结构特性及基团贡献法预测沸点的研究[D].北京:中国石油大学,2003.