Best Practices in Evaluating Production Performance: A Niger Delta Case Study with Inter-Reservoir Communication

Abstract

Uncertainty management for resource volume of a brown field is relevant. An analytical approach via dynamic model was used to evaluate this impact on a developed gas reservoir (brown) by two other reservoirs. One of them is a green oil-rim reservoir, while the other is a developed oil reservoir. This is due to sand-to-sand juxtaposition with the two reservoirs. Integration of available data over time, while considering all the reservoir uncertainties was adopted. This was buttressed by the continuous production from the gas reservoir, that had already gone past the initially evaluated Gas Initially in Place (GIIP). The brown reservoir is a highly faulted gas reservoir with twenty-seven (27) years production history, by seven wells. The reservoir's GIIP re-evaluation had been done twice over the years. This was because it had fully developed its ultimate recovery, with three wells still producing. This GIIP re-evaluation approach could no longer be utilized, as it had very good well coverage. Fault seal analysis, pressure, PVT sample and log data taken over time reveal the likelihood of communication across the stacked reservoirs. A multi-tank material balance model (MBAL) was built via a multidisciplinary approach. The model was history matched using an experimental design approach that saved time and contacts were calibrated. The result showed the quantity of hydrocarbon in both reservoirs that have flowed into the developed gas reservoir. This provides a snapshot on the resource volume impact of the reservoirs with respect to their development and uncertainty management. Revised development plans and resource booking for the reservoirs are also study outcomes. This is relevant for business decisions on resource volume booking and reservoir management. This approach is a quick win within the Well, Reservoir and Facility Management (WRFM) workspace. Further work by building a 3D simulation model and pressure data acquisition is required for robust benchmarking.