Validation of applying stochastic geostatistical algorithms in electrofacies modeling in Sarvak reservoir of an Iranian oilfield

In this study, electrofacies analysis has been done using MRGC (Multi-resolution graph-based clustering) method to be used in static modeling. Then, the resulting facies was modeled and compared together by applying different geostatistical stochastic algorithms in Petrel software. Two electrofacies classes including reservoir and non-reservoir facies were determined which were used for facies modeling. Seismic data was also applied for seismic facies construction and also to construct trend maps for appropriate facies distribution. In order to investigate the effect of five applied different geostatistical algorithms used in facies modeling on porosity distribution, the constructed facies models were used for porosity modeling. According to this study, the uncertainty of electrofacies modeling without applying seismic data increases which in turn reduces the accuracy of porosity models. In addition, electrofacies modeling considering the sequential indicator simulation (SIS) algorithm and applying the seismic trend maps, enhance the accuracy of the porosity model. Moreover, construction the of seismic facies is considered the best method for facies modeling to be used for porosity modeling due to the high correlation coefficient between acoustic impedance and porosity.