Document Type : Original Research Paper
Authors
1 College of Engineering, School of Chemical Engineering , University of Tehran, Tehran, Iran
2 Sharif University, Dep. of Chemical and Petroleum Engineering, Tehran, Iran
3 slamic Azad University, Science & Researches Branch, Dep. of Petroleum Engineering, Tehran, Iran
Abstract
Determination of different facies is one of the important and basic tasks of geological engineering characterization of reservoir rocks from well logs and core data. Our objective is to identify and determine different facies of the South Pars Field using RBF and PNN neural networks in order to perform static and dynamic simulation. These networks are utilized to identify facies of the South Pars Field for the first time in Iran. In this study, we use different parameters of mentioned networks such as ‘spread’ and ‘goal numbers’ to improve networks operation. In this regards, the optimum values of these two parameters were 0.01-10 and 0.02-0.04 respectively. The results show that the RBF and PNN neural networks are robust means to determine and model the facies of the South Pars Field in Iran.
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