Challenges of combining field outcrops and E-logs to improve oil recovery in Cenomanian reservoirs, North Silah deep field, Western Desert, Egypt

Abstract

The Upper Cretaceous Abu Roash Formation in Egypt's Western Desert exhibits highly variable depositional environments, including fluvial, aeolian, tidal, and shoreface systems. This heterogeneity poses major challenges for predicting facies distribution, targeting new wells, and managing production. Conventional E-log-based interpretations typically focus on lithology, which lacks the spatial and geometrical resolution necessary for robust reservoir modeling. This study presents a novel workflow for 3D static modeling that integrates surface facies analogs with subsurface E-log data. Sedimentary structures and facies associations from the Abu Roash "G" Member type locality were analyzed to establish characteristic gamma ray (GR) responses for each facies. These GR signatures form a predictive interpretation scheme, enabling consistent facies identification in North Silah Deep Field wells. The interpreted facies logs were distributed using a deterministic modeling approach, constrained by the field's conceptual depositional model and available reservoir data. The resulting static model incorporates porosity and water saturation, providing a detailed framework for volumetric calculations and supporting dynamic simulation. This methodology improves facies prediction in complex, heterogeneous reservoirs and offers a transferable approach for other stratigraphically and texturally diverse systems. By directly linking surface analogs to subsurface logs, it bridges the gap between sedimentological analysis and reservoir characterization, enhancing the accuracy of geological models and supporting more informed field development strategies.