A 3D geological model is an essential step to reveal reservoir heterogeneity and reservoir properties distribution. In the present study, a three-dimensional geological model for the Mishrif reservoir was built based on data obtained from seven wells and core data. The methodology includes building a 3D grid and populating it with petrophysical properties such as (facies, porosity, water saturation, and net to gross ratio). The structural model was built based on a base contour map obtained from 2D seismic interpretation along with well tops from seven wells. A simple grid method was used to build the structural framework with 234x278x91 grid cells in the X, Y, and Z directions, respectively, with lengths equal to 150 meters. The total number of grids is (5919732) in the geological model. CPI (computer-processed interpretation) for 7 wells contain (facies, porosity, water saturation, and NTG) was imported to Petrel 2016 software. Facies log was upscaled and distributed along the 3D grid. Truncated Gaussian with trend method was used to distribute the facies taking into account the conceptual facies model of the Mishrif formation. The result shows that the trend of sedimentation suggests a retrogradation pattern from NW to SE. Facies1 (Reservoir), dominated by Limestone brown to light brown, with oil shows has good distribution within the area and thinning towards the NW. The petrophysical properties (porosity, water saturation, NTG, and permeability) were distributed using the Sequential Gaussian Simulation (SIS) method and the facies model as a guide for distribution. The results show that petrophysical properties enhanced in the southeast area, representing the reef region compared to the northwest side of the study area. Unit Mishrif B had the highest porosity value and lower water saturation value along the entire field. While the units Mishrif B1, B2, and B3 show a gradual decrease in reservoir properties towards the field's southeast side. The results also show that the conceptual facies model has great benefit in constructing the 3D geological model, reflecting the geological knowledge used to correctly distribute the reservoir properties (porosity and water saturation).
Receipt Date:10/11/2021 Acceptance Date:29/12/2021 Publication Date:31/12/2021
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