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

Authors

1 Ph. D. student of Petroleum exploration engineering, Dept., of Petroleum Engineering, Amirkabir University of technology, Tehran, Iran

2 Prof., Dept., of Petroleum exploration engineering, Dept., of Petroleum Engineering, Amirkabir University of technology, Tehran, Iran

3 Assoc. Prof., Dept., of Geology, Faculty of science, University of Tabriz, Tabriz, Iran

4 Sarvak Azar Engineering and Development Company (SAED), Tehran, Iran

Abstract

Constructing different facies models is necessary in reservoir static modeling to consider the effect of geology and sedimentology and also control the geostatistical distribution of petrophysical properties. 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 were modeled and compared together by applying different geostatistical stochastic algorithms in Petrel software. Based on electrofacies analysis, first five electrofacies (including two non-reservoir facies and three reservoir facies) were identified. In order to compare the effect of different facies distribution algorithms, three reservoir facies and two non-reservoir facies were combined and then two resulted facies were distributed as reservoir and non-reservoir facies in 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 via considering the sequential indicator simulation (SIS) algorithm and applying the seismic trend maps, enhance the accuracy of the porosity model. Moreover, this study showed, construction the seismic facies is the best method for facies modeling to be used for porosity modeling due to the high correlation coefficient between acoustic impedance and porosity.

Keywords

References

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History

  • Receive Date: 30 October 2022
  • Revise Date: 25 May 2023
  • Accept Date: 27 May 2023

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