Abstract
In this paper, based on dual-energy broad beam gamma ray attenuation technique (using two transmission 1-inch NaI detectors and a dual-energy gamma ray source), an artificial neural network (ANN) model was used in order to predict the volume fraction of gas, oil and water in three-phase flows independent of the flow regime. A multilayer perceptron (MLP) neural network was used for developing the ANN model in MATLAB 8.1.0.604 software. The input parameters of the MLP model were registered counts under first and second full energy peaks of the both transmission NaI detectors, and the outputs were gas and oil percentage. The volume fractions were obtained precisely independent of flow regime using the presented model. Mean absolute error of the presented model was less than 2.24%.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
