Application of 4D Seismic in an Integrated Approach to Reservoir Characterization and History-Matching to Locate Waterflood Front and Remaining Oil for Optimized Recovery in a Complex Deepwater Oilfield

Abstract Time-lapse seismic (4D seismic) has emerged as a critical tool in understanding reservoir dynamics, particularly in complex deep-water turbidite sandstone systems. The application of 4D seismic in the Niger Delta's deep-water turbidite reservoirs has significantly enhanced reservoir management and further development, particularly in modeling waterflood fronts and identifying remaining and/or by-passed oil. This study explored the integration of 4D seismic data into reservoir performance history matching for modeling waterflood fronts and identifying bypassed or remaining oil. Deep-water turbidites are characterized by heterogeneous and high-permeability channel systems, leading to challenges in predicting waterflood efficiency and ultimate recovery. By combining 4D seismic with dynamic reservoir simulation, key insights into saturation changes (remaining oil), reservoir connectivity, and fluid flow pathways were obtained. This workflow involved processing an Ocean-Bottom-Node (OBN) 4D seismic data to extract changes in acoustic impedance, which were linked to saturation and pressure variations. These changes were then incorporated into the reservoir performance history matching to refine the reservoir model, ensuring better alignment with observed production and injection data. The seismic-derived waterflood front tracking enhanced the understanding of the reservoir sweep efficiency and flood front location, highlighting areas with bypassed oil due to intra-reservoir heterogeneities, stratigraphic barriers, sub-seismic faults, or suboptimal well placement. This integrated approach has been used in the Ufoma deepwater oilfield further development as a case study. It did not only improve the accuracy of the existing 3D Earth reservoir models but also supported the optimization of the field development strategy by successfully targeting the remaining oil pockets in the further development project for the reservoir. It also led to improved reservoir characterization and modeling in the Ufoma field reservoir management (i.e., WRFM - History Matching and Prediction) and has proven to be a valuable tool in maximizing hydrocarbon recovery in these complex geological channel sands bodies. This work further demonstrates the efficacy of this integrated approach, leading to improved well placement for maximum oil recovery and optimized field development strategies for the Ufoma oilfield in deepwater Niger-Delta.