Building an accurate static model for entire field was the primary objective in the reservoir characterization and simulation. The goal was to develop a model with sufficient detail to represent reservoir discontinuity and petrophysical properties in field scale. There are different geostatistical methods for petrophysical modeling. Sequential Gaussian simulation (SGS) is a kriging based algorithm which simulates nodes after each other sequentially, subsequently using simulated values as a conditioning data. It is necessary to use standard Gaussian values in SGS method. Collocated Cokriging (C.C) is a reduced form of Cokriging, which requires knowledge of only the hard data covariance model, the correlation coefficient between the hard and soft (auxiliary) data, and the variances of the two attributes. In this study, porosity and permeability of a heterogeneous gas condensate carbonate reservoir are modeled first by SGS method. Than seismic attributes with high distribution density but low resolution are used as an auxiliary variable for porosity modeling from well logs data (limited distribution but high resolution).Determining which seismic attributes are meaningful to assist in the modeling and estimation process requires statistical analysis. In second step the modeled porosity by C.C is used as an auxiliary variable for permeability modeling. So in this method, seismic attributes have an indirect role in permeability modeling as well. A common practice usually involves the use of a cross validation scheme, where each well is removed sequentially, and its property is predicted using information from the remaining wells.