Sedimentary facies architecture and terminal fan systems of the lower Palaeogene Shahejie formation in Bonan Sag, Bohai Bay Basin, China: implications for hydrocarbon exploration

In the search for oil reservoirs within the lower fourth member of the Paleogene Shahejie Formation (Es4x), understanding the depositional model is crucial, particularly in the Bonan Sag of the Bohai Bay Basin. Previous studies have provided limited perspectives on the depositional mechanisms in complex geological settings characterized by tectonic orogeny, volcanic activity, and metamorphism. This research seeks to address this knowledge gap by focusing on sedimentary deposits formed by the terminal fan system, diverging from the more commonly studied fan delta models. This study aims to clarify the depositional environment and mechanisms of the Es4x Member by identifying and characterizing the sedimentary facies and exploring how provenance influences the distribution of sandstone reservoirs in this heterogeneous formation. Data from more than 20 wells and over 500 m of cores revealed 15 lithofacies types, which were grouped into five facies associations (FA1--FA5) and used to describe the depositional architecture. These subfacies are categorized into feeder, distributary, and basal zones, with proximal, medial, and distal subfacies. Lithological analysis identified the dominant rock types as lithic arkose, feldspathic litharenite, and litharenite. The results show that the medial subfacies dominates the Bonan Sag during the deposition of the Es4x Member, occasionally extending towards the basinal zone through sporadic diffuse flood channels. This depositional mechanism reflects ephemeral water stretches influenced by varying weather conditions. Volcanic clasts distributed beyond the terminal fan system further illustrate the influence of volcanic activity on depositional processes. This study provides key findings on the sedimentary mechanisms in the Es4x Member, offering important information regarding deep reservoirs in tectonically active areas, particularly the challenges of predicting oil reservoirs in thin versus thick red beds.