Abstract— Geostatistical modeling technicality hasutilized to build the geological models before scaling-up. Possible images of the area under investigation have provided from these methods that honor the well data and have the same variability computed from the original data. Property modeling is the process of filling the cells of the grid with discrete (facies) or continuous (petrophysics) properties. When interpolation between data points, propagate property values along the grid layers have executed. The main branch in the modeling algorithms obtainable is between Deterministic and Stochastic methods in Petrel. Both kinds of algorithms are available in the Facies and Petrophysical modeling processes.The process of well log up scaling is required to post values in each cell of the 3D grid where each of the wells is situated; to achieve these averages well properties are used to populate each of the cells. Three Dimension modeling has built depending to 12 wells for Mishrif formation in Amara oil field. All wells have PHIE and Water Saturation logs, which exported from interactive petrophysics software. Thereafter, scale up well logs has carried out for these wells. To building the model, there are different methods of distribution of petrophysical properties. Eight methods have executed in order to propagate property values through construct Porosity and Water Saturation Models. Depending on the results, there are not data from the modeling corresponding exactly to the true data from the log interpretation for the same well, but it approximate from the true data in different percentage .Sequential Gaussian Simulation suitable algorithm method to build the 3D modeling for Mishrif formation.
Keywords— Deterministic algorithms, Mishrif Formation, Petrophysical properties, Reservoir modeling, stochastic algorithm.
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