Reservoir facies and porosity modeling using seismic data and well logs by geostatistical simulation in an oil field
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ORIGINAL ARTICLE
Reservoir facies and porosity modeling using seismic data and well logs by geostatistical simulation in an oil field Asieh Zare1 · Majid Bagheri2 · Mohammadreza Ebadi1 Accepted: 29 May 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Reservoir characterization of petroleum reservoirs can be claimed as one of the most important parts of reservoir management for optimized production and future developments. Through reservoir evaluation, geological zoning for a better comprehension of subsurface structure is needed. For developing a model, porosity plays a vital role; there are two common methods for obtaining this parameter, core samples and well logging. However, the results of these methods are in well scale which cannot be used through field scale modeling. A solution can be the combining seismic field data well log data, which makes it possible to estimate the reservoir properties in field scale. In this study, multi-attribute analyses were applied based on multilayer perceptron to determine the reservoir facies alteration and heterogeneity in the Ghar reservoir of the Hendijan oil field located in the Persian Gulf. Facies modeling was done through the sequential indicator simulation (SIS) algorithm which coupled with the possible trend and indicator kriging (IK) as geostatistical methods. Within the comparison of these two generated models with core facies, the obtained accuracy of SIS algorithm coupled with the possible trend and indicator kriging are 94% and 72%, respectively. Porosity distribution was also done by the sequential Gaussian simulation (SGS) algorithm which resulted the average porosity of 18% in Ghar formation. The SIS method results are compatible with the porosity distribution model obtained from the SGS simulation. The final results prove the robustness of the applied methods for facies and porosity modeling. Keywords Porosity · Facies modeling · Sequential indicator simulation · Sequential gaussian simulation · Seismic data
Introduction Reservoir porosity is a critical parameter for petroleum exploration and production. Reservoir porosity determines the hydrocarbon storage capacity (Wang 2017). Facies is a body of rock characterized by particular combination of lithology, physical, and biological structures that bestow an aspect (facies) different from the bodies of the rock above, below, and laterally adjacent (Sarkar and Banerjee 2020). * Majid Bagheri [email protected]; [email protected] Asieh Zare [email protected] Mohammadreza Ebadi [email protected] 1
Department of Petroleum Engineering, Petroleum University of Technology, Abadan, Iran
Institute of Geophysics, University of Tehran, PO Box, 14115‑6466 Tehran, Iran
2
The well logs data cannot individually describe the variations in the reservoir petrophysical properties. This is due to the oil field distribution that is scattered and their size in comparison with the heterogeneity dimensions is very large for modeling (Kyi 2014). The well data are so scattere
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