Prediction of the MMP of gases using neural networks
Publish place: 07th International Congress on Chemical Engineering
Publish Year: 1390
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
ICHEC07_655
تاریخ نمایه سازی: 25 فروردین 1394
Abstract:
Miscible gas injection is one of the most effective methods in enhancing oil recovery.The most important Parameter in the design of such processes is minimum miscibility pressure (MMP).MMP is the lowest pressure that can be injected through multi contact with reservoir fluid to be miscible. MMP can be obtained from Rising bubble apparatus, s lim tube and mixing cell in laboratory that these methods are costly and time consuming. A multilayer perceptron neural networks with 6 neuron of input layer, 12 neuron of hidden layer and a neuron of output layer was trained for estimating the MMP. The coefficent of determination (R2) between experimental MMP and predicted MMP using neural networksfor the training data, testing data and all data were 0.988, 0.954 and 0.970 respectively. The results states neural networks has higher accuracy that Alston method in predicting MMP.
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Authors
Mohammad Sadegh momeni
Department of Petroleum engineering, Omidiyeh branch, Islamic Azad University Omidiyeh, Iran Author’s address:
nasser teymourei khanesary
Corresponding Author’s Gas engineering, Petroleum University of Technology-Ahwaz
alireza khoshroo
University of Yasouj, Yasouj, Iran