TY  - BOOK
AU  - Abdelrigeeb Ali Algathe                                            
AU  - Ahmed Hamdy Elbanbi , 
AU  - Khaled A, Elmetwally , 
AU  - Khaled Ahmed Abdelfattah , 
TI  - Development artificial intelligent systems for black oil pvt properties prediction / 
PY  - 2015///
CY  - Cairo : 
PB  - Abdelrigeeb Ali Algathe , 
KW  - Expert System
KW  - Hybrid
KW  - Oil Properties
N1  - Thesis (Ph.D.) - Cairo University - Faculty of Engineering - Department of Metallurgical Engineering; Issued also as CD
N2  - In absence of PVT laboratory experiments data on representative fluid samples, it is usually difficult to choose the appropriate PVT correlations to calculate oil PVT properties. This difficulty will be increase when input data to PVT correlations (oil API gravity, initial gas-oil ratio, specific gravity of separator gas and temperature) vary along the flow from one section to the other in the production system. In this research, two Hybrid models and one Expert System Artificial Intelligent (AI) approaches are introduced for solving this problem. The proposed approaches are based on clustering the PVT data into several groups. According to this study, expert guidelines are proposed to select an appropriate correlation for each oil properties. The guidelines for using hybrid AI and the best configuration are also added for calculating oil PVT properties
UR  - http://172.23.153.220/th.pdf
ER  -