Author(s): ELRADI ABASS | CHENG LIN SONG
Journal: Journal of Engineering Science and Technology
ISSN 1823-4690
Volume: 6;
Issue: 5;
Start page: 628;
Date: 2011;
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Keywords: Oil recovery method | Artificial intelligence | Expert system | Screening criteria | EOR parameters
ABSTRACT
This paper describes the application of an Artificial Intelligence (AI) technique to assist in the selection of an Enhanced Oil Recovery method (EOR). The structure of an expert systems selection based on a new formulated screening criteria, Artificial Intelligence selection developed by a computer software called (EKORA), with an easily and friendly user interface by using visual Basic-6 environment tools is presented. An additional capability provided by this software is the ability of changing and editing the parameters of EOR methods which emerged or tested in current implementation projects. Other commercial expert systems either offer limited or no capabilities for changing and editing the EOR parameters of screening rule.
Journal: Journal of Engineering Science and Technology
ISSN 1823-4690
Volume: 6;
Issue: 5;
Start page: 628;
Date: 2011;
VIEW PDF
DOWNLOAD PDF Original pageKeywords: Oil recovery method | Artificial intelligence | Expert system | Screening criteria | EOR parameters
ABSTRACT
This paper describes the application of an Artificial Intelligence (AI) technique to assist in the selection of an Enhanced Oil Recovery method (EOR). The structure of an expert systems selection based on a new formulated screening criteria, Artificial Intelligence selection developed by a computer software called (EKORA), with an easily and friendly user interface by using visual Basic-6 environment tools is presented. An additional capability provided by this software is the ability of changing and editing the parameters of EOR methods which emerged or tested in current implementation projects. Other commercial expert systems either offer limited or no capabilities for changing and editing the EOR parameters of screening rule.