Facies Modeling using Back-propagation Neural Networks In Southern Pars Field

Determination of different facies is one of the most important and fundamental tasks of geological and engineering characterization of reservoir rocks. The neural network method is one of the new techniques used in identification of facies. The objective of the present study was to identify and measure different facies of Southern Pars gas and oil fields (Iran) using back-propagation neural networks in order to develop static and dynamic models. Modeling was carried out using three different techniques. Also network parameters were optimized in order to improve the network performance including number of layers and neurons, transfer function, training algorithm, dividing and performance functions. The results indicate that the back-propagation neural network is a powerful method for identification and modeling of the facies.