Abstract The Prediction of the reservoir characteristics from seismic amplitude data is a main challenge. Especially in Nile Delta Basin, where subsurface geology complex and reservoirs are highly heterogeneous. Modern characterization methodologies spanning around attributes analysis, deterministic stochastic inversion methods, Amplitude Variation with Offset (AVO) interpretations, stack rotat...

there are two methods for identifying formation interface in oil wells: core analysis, which is a precise approach but costly and time consuming, and well logs analysis, which petrophysists perform, which is subjective and not completely reliable. in this paper, a novel coupled method was proposed to detect the formation interfaces using gr logs. second approximation level (a2) of gr log gained...

Abstract The identification of lithology, fluid types, and total organic carbon content are great priority in the exploration unconventional hydrocarbons. As a new alternative, further developed K-means type clustering method is suggested for evaluation shale gas formations. traditional approach cluster analysis mainly based on use Euclidean distance grouping objects multivariate observations i...

3D modeling method is divided into geospatial modeling and 3D geological modeling. 3D geological modeling technique has become a favorable tool for people to observe and analyze the geological body enriched in mineral resources. Unlike geospatial modeling, 3D geological modeling must consider various geological conditions affecting spatial shape and petrophysical distribution of geological body...

Estimation of fluid saturation is an important step in dynamic reservoir characterization. Machine learning techniques have been increasingly used recent years for prediction workflows. However, most these studies require input parameters derived from cores, petrophysical logs, or seismic data, which may not always be readily available. Additionally, very few incorporate the production reflecti...