The main challenge of modeling the glacial sandstone deposits is capturing the property pattern in the reservoir, because of the abrupt changes from one depositional environment to another. This reservoir heterogeneity impacts the infill well planning and production performance of the field. In this research, a comprehensive workflow is presented to model the spatial distribution of porosity and permeability within the Mamuniyat sandstone in the Murzuq Basin, Onshore Libya, using geostatistical techniques. Geostatistical techniques in combination with the available information from six wells using geological information, petrophysical analysis, and seismic interpretation were used to construct a 3D model for the reservoir. The structural input included the main interpreted horizons, with a total of 34 faults. Six facies were identified in the reservoir, dominated mainly by the Outwash Fan and Submarine Channel. To categorize reservoir quality, four rock types were defined based on the observed relationship between porosity and permeability. Variogram analysis was performed to describe the spatial relationship between all reservoir layers. Sequential Gaussian Simulation was utilized for porosity modeling and Gaussian Random Function Simulation for Permeability were both constrained to facies. Water saturation was modeled based on the height function method for each rock type. The final model revealed significant variation in reservoir characteristics; this variability is attributed to the diagenetic process that affects the reservoir quality of the sandstone. The best reservoir characteristic was encountered in structural highs, where the most productive wells had been drilled in the area. The incorporation of more data such as core analysis, seismic attributes, and the engineering information in the model will be useful to better understanding of reservoir quality, thus improves future development decisions for the field.

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