Abstract

Deepwater turbidite reservoirs are important targets for modern oil exploration, but it's hard to describe them because of their complicated depositional architecture, limited well control, and different reservoir properties. This systematic review looks at different ways to describe reservoirs in deepwater turbidite systems, focusing on the Niger Delta Fold Belt in particular. We combine methods like seismic attribute analysis, well log integration, and dynamic data validation to come up with the best ways to lower geological uncertainty. The Niger Delta Fold Belt is a great example of how integrated workflows work because it has complicated structural deformation and a lot of turbidite sequences. The main results show that combining multi-attribute seismic analysis with geostatistical well log interpretation and calibrated dynamic modeling greatly improve the ability to predict the shape, connectivity, and performance of a reservoir. This review delineates significant deficiencies in existing methodologies and suggests prospective research trajectories for enhancing deepwater reservoir characterization.