Porosity is one of the most important petrophysical properties that plays an effective role in better understanding the hydrocarbon reservoir. One of the common methods for examining the reservoir in terms of lithology and porosity is the seismic inversion method and the use of seismic attributes. In this article, the results obtained from the prestack seismic data inversion of the area covered by 2-D seismic in Fahlian Garou Formation in Arash field along with density, sound and porosity wells were used. Using the relationship between acoustic impedance due to seismic inversion and porosity in the well, the production of porosity has been estimated by multi-attribute methods and artificial neural network