Porosity is one of the important parameters in the reservoir engineering, which enables experts for developing oil and gas fields. The use of core samples and well logging are the common methods. By seismic and well log data it is possible to estimate reservoir properties of farther distances from well sites. In this study, multi-attribute analyses were applied based on ANN methods and well logs data to determine the reservoir facies alteration in the Ghar reservoir of the Hendijan oil field. Facies modeling by the Sequential Indicator Simulation (SIS) algorithm was performed for each facies and porosity modeling by the Sequential Gaussian Simulation (SGS) algorithm was performed. The results are illustrating the facies modeling with the SIS algorithm and the estimation of porosity with this algorithm are adaptive with the final porosity model obtained with the SGS simulation algorithm and the average porosity in Ghar formation is 18%.