The Prediction of the reservoir characteristics from seismic amplitude data is a main challenge. Especially in the Nile Delta Basin, where the subsurface geology is complex and the reservoirs are highly heterogeneous. Modern seismic reservoir characterization methodologies are spanning around attributes analysis, deterministic and stochastic inversion methods, Amplitude Variation with Offset (AVO) interpretations, and stack rotations. These methodologies proved good outcomes in detecting the gas sand reservoirs and quantifying the reservoir properties. However, when the pre-stack seismic data is not available, most of the AVO-related inversion methods cannot be implemented. Moreover, there is no direct link between the seismic amplitude data and most of the reservoir properties, such as hydrocarbon saturation, many assumptions are imbedded and the results are questionable. Application of Artificial Neural Network (ANN) algorithms to predict the reservoir characteristics is a new emerging trend. The main advantage of the ANN algorithm over the other seismic reservoir characterization methodologies is the ability to build nonlinear relationships between the petrophysical logs and seismic data. Hence, it can be used to predict various reservoir properties in a 3D space with a reasonable amount of accuracy. We implemented the ANN method on the Sequoia gas field, Offshore Nile Delta, to predict the reservoir petrophysical properties from the seismic amplitude data. The chosen algorithm was the Probabilistic Neural Network (PNN). One well was kept apart from the analysis and used later as blind quality control to test the results.

The Sequoia Pliocene channel reservoirs within the West Delta Deep Marine (WDDM) concession, located offshore of the Nile Delta, pose significant challenges due to their complex stratigraphy and variable reservoir properties. This study employs an integrated approach, combining seismic data interpretation with comprehensive petrophysical analysis, to characterize these reservoirs and assess their hydrocarbon potential. Seismic data interpretation revealed a complex depositional environment, characterized by an upward-fining sequence of sandstones and mudstones. High seismic amplitudes were associated with gas sands, while lower amplitudes indicated background shale. The seismic stratigraphy indicates that the Sequoia channel system evolved from an initial high-energy erosional phase to a more subdued depositional environment, leading to significant heterogeneity in the reservoir quality. Petrophysical analysis demonstrated that effective porosity values within the reservoir range from 18 to 30%, with water-saturation levels of between 38 and 68%, reflecting the variability in reservoir properties across different zones. The calculated gas initially in place (GIIP) for the Sequoia channel ranges from 724.1 to 4158.71 Bcf, highlighting the substantial hydrocarbon potential within this complex system. This study underscores the importance of integrating seismic and petrophysical data to develop a comprehensive understanding of the Sequoia channel reservoirs. The results provide a robust framework for optimizing field development strategies, which is crucial for maximizing hydrocarbon recovery. The findings also offer valuable insights into the geological complexities of the WDDM concession, serving as a reference for future exploration and production efforts in similar deep-water environments.

The Gulf of Suez is a sedimentary rift-basin with thick evaporites and complex structural settings that presents challenges to achieving quality imaging based on seismic reflection data. Such subsurface settings and the lack of 3D seismic data poses challenges in building reservoir models to guide hydrocarbon exploration and development, especially in southern parts the Gulf of Suez. This study attempts to overcome the challenges of both 2D seismic interpretation and building a static reservoir model of two Miocene reservoir formations, Ras Ghara Field, Southern Gulf of Suez. Integration of well log data analysis of nine wells and regional-tectonics cognizant 2D seismic interpretation of nineteen 2D seismic lines enabled a reliable 3D static reservoir model. The Miocene reservoir characterization reveals heterogeneity in lithofacies distribution, with thick evaporite sequences causing seismic reflection distortions. Significant hydrocarbon accumulations are associated with horst fault blocks. The Miocene reservoirs demonstrate effective porosity of 14-33%, water saturation of 16-65%, and hydrocarbon saturation of 35-84%. Two new prospects are identified based on structure, facies distribution, and petrophysical results, with estimated original oil in place (OOIP) of 2,002,404 stock tank barrels (STB) and 1,175,580 STB for the Kareem Formation, and 6,302,916 STB and 2,841,894 STB for the Rudeis Formation.

The lithological dichotomy in the Hammam Faraun Member (Gulf of Suez, Egypt) reveals a stable western flank with Nullipore carbonate deposits, contrasting with the clastic-prone eastern margin influenced by tectonic activity. This study aims to decipher multifactorial controls on spatial lithological variability and reservoir implications through (1) foraminiferal-based paleoenvironmental reconstruction; (2) integrated sequence stratigraphic–petrophysical analysis for sweet spot identification; and (3) synthesis of lateral facies controls. This study uniquely integrates foraminiferal paleoenvironmental proxies, sequence stratigraphy, and petrophysical analyses to understand the multifactorial controls on spatial variability and its implications for reservoir characterization. Middle Miocene sea surface temperatures, reconstructed between 19.2 and 21.2 °C, align with warm conditions favorable for carbonate production across the basin. Foraminiferal data indicate consistent bathyal depths (611–1238 m) in the eastern region, further inhibited in photic depths by clastic influx from the nearby Nubian Shield, increasing turbidity and limiting carbonate factory growth. Conversely, the western shelf, at depths of less than 100 m, supports thriving carbonate platforms. In the sequence stratigraphy analysis, we identify two primary sequences: LA.SQ1 (15.12–14.99 Ma), characterized by evaporitic Feiran Member deposits, and LA.SQ2 (14.99–14.78 Ma), dominated by clastic deposits. The primary reservoir comprises highstand systems tract (HST) sandstones with effective porosity ranging from 17% to 22% (calculated via shale-corrected neutron density cross-plots) and hydrocarbon saturation of 33%–55% (computed using Archie’s equation). These values, validated in Wells 112-58 (ϕe = 19%, S_hc = 55%) and 113M-81 (ϕe = 17%, S_hc = 33%), demonstrate the primary reservoir potential. Authigenic dolomite cement and clay content reduce permeability in argillaceous intervals, while quartz dissolution in clean sands enhances porosity. This research emphasizes that bathymetry, sediment availability, and syn-sedimentary tectonics, rather than climate, govern carbonate depletion in the eastern region, providing predictive parameters for identifying reservoir sweet spots in clastic-dominated rift basins.