Estimating phase behavior of the asphaltene precipitation by GA-ANFIS approach

被引：2

作者：

Chen, Mengxiang ^{[1
]}

Sasanipour, Jafar ^{[2
]}

Mousavy, Sayyed Ali Kiaian ^{[3
]}

Khajeh, Ebrahim ^{[4
]}

Kamyab, Majid ^{[5
]}

机构：

[1] Guangdong Polytech Environm Protect Engn, Dept Mech & Elect Engn, Foshan 528216, Peoples R China

[2] Petr Univ Technol, Ahwaz Fac Petr Engn, Dept Gas Engn, Ahvaz, Iran

[3] Sharif Univ Technol, Dept Comp Engn, Tehran, Iran

[4] Univ Teknol Malaysia, Fac Comp, Skudai, Johor, Malaysia

[5] Iran Univ Sci & Technol, Sch Chem Engn, Comp Aided Proc Engn Lab Cape, Tehran, Iran

来源：

PETROLEUM SCIENCE AND TECHNOLOGY | 2018年 / 36卷 / 19期

关键词：

ANFIS; asphaltene; dilution ratio; heavy n-alkane; temperature; SCALING EQUATION; MOLECULAR-WEIGHT; OIL; HYDROCARBONS; TEMPERATURE; PREDICTION; SOLUBILITY; ONSET; GASES;

D O I：

10.1080/10916466.2018.1493503

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

This study implements an adaptive neuro-fuzzy inference system (ANFIS) approach to predict the precipitation amount of the asphaltene using temperature (T), dilution ratio (R-v), and molecular weight of different n-alkanes. Results are then evaluated using graphical and statistical error analysis methods, confirming the model's great ability for appropriate prediction of the precipitation amount. Mean squared error and determination coefficient (R-2) values of 0.036 and 0.995, respectively are obtained for the proposed ANFIS model. Results are then compared to those from previously reported correlations revealing the better performance of the proposed model.

引用

收藏

页码：1582 / 1588

页数：7

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