Assessing the production potential of Niger Delta reservoirs under uncertainty using numerical simulation tools

The Niger Delta region is known as a major hub of oil reserves in the world. However, most studies emphasize exploration and static characterization, with limited attention to the dynamic production behavior and uncertainty management of its reservoirs. Using static models as a foundation, reservoir engineering tools offer an opportunity to address this gap by simulating fluid flow and production under defined production setups, and uncertainty. This study employs numerical reservoir simulation to evaluate the production potential of a representative model of Niger Delta reservoir during its development phase, accounting for geological uncertainties. Polynomial regression, as a proxy model, enabled efficient Monte Carlo-based probabilistic simulations with verified accuracy (R2 > 0.92 and <3% relative error). The findings revealed substantial oil production with excellent production sustainability, primarily driven by aquifer support through water influx, with minimal pressure decline. However, significant risks associated with wide variations in oil production under uncertainties were identified, highlighting the importance of incorporating uncertainty reduction techniques such as data assimilation. The systematic integration of aquifer support within a probabilistic framework provides a novel and replicable approach for evaluating reservoir performance and guiding risk-informed development planning in the Niger Delta and analogous siliciclastic systems.