sajjad sarallah zabihi - ZPA and PEDEX company
seyedabolfazl miri - exploration directorate
meyssam tavakkili - petroleum university of technology

facies modeling is the first , most essential and complicated stage in reservoir characterization and static modeling , deterministic and stochatic approaches are two common ways to represent spatial variability of facies. In the case where the amount of data is not too much stochastic method such as sepuential indicator simulation generates a noisy 3Dmodel and also deterministic approach such as kriging produce a very smooth 3D facies model in this paper in order to generate an accurate 3D facies model some probability maps by ordinary kriging were made and were used as a 2 D trend in SIS algorithm to generate a reasonable facies model. in this study the faceis were defined based on petrophysical and geological data. special cutoffs for lithology logs integrated with MPGC algorithm was used to define faceis. sequential indicator simulation algorithm was applied to simulate ten realizations and then statistical parameters of raw data and model were compred. also E-type model for these ten realizations was generated by averaging them using most -of method.

electrofacies , MRGC, trend maps , stochastic , SIS