Rock typing of the Miocene Hammam Faraun alluvial fan delta sandstone reservoir using well logs, nuclear magnetic resonance, artificial neural networks, and core analysis, Gulf of Suez, Egypt

The application of integrated methods to evaluate the quality of reservoir rocks is becoming crucial in petroleum geoscience. The Miocene reservoirs in the El Morgan Oil Field consist mainly of sandstones with interbedded dolomitic silts and shales. Based on the pore scale, the sandstone reservoir of Hammam Faraun Member is a heterogeneous reservoir, and this is the main challenge in this oil field that affects both production and exploration activities. In this article, we have integrated the well logs, nuclear magnetic resonance (NMR), artificial neural networks (ANN) and core analysis to better understand these alluvial fan sandstone reservoirs. The petrographic description indicates arkosic sandstone with varied pore types, texture, cement, and sorting. The studied flow and storage capacity for well#1, indicate four rock types with 24 flow units and eleven barriers, which indicates a high degree of heterogeneity. The artificial neural networks (ANN), that is, the K.mod module, were used to enhance the prediction quality and forecast of FZI in the uncored intervals, where the NMR-calculated permeability acts as a calibration point for the FZI model validation. This study reveals that the FZI is controlled by permeability, which is mostly influenced by pore throat size. The NMR log showed varied free fluid volume with varied capillaries, clay-bound volumes and minor streaks of tar along the studied unit. The reservoir pores in the study area are residual pores that have undergone mechanical compaction and cementation that reduce porosities, while dissolution enhances the sandstone porosities. Porosity and permeability were significantly reduced in the presence of clays and carbonate minerals, which indicates poor reservoir quality zones in some parts. The primary factor influencing permeability is pore throat size, which is heavily influenced by the depositional environment and subsequent diagenetic processes. The findings of this study could lead to the development of accurate reservoir static models for future exploration and development plans in the studied area and elsewhere in similar depositional settings.