Onyeanusi Peter Obinna¹, Udoh Monday Udofia², Imasuen I O¹, Tsaku Stephen³, Omodolor Hope E^1,, Aduomahor Benedict Oghenemaro¹

Detailed analyses of geological, petrophysical and seismic datasets were employed in other to determine the effect of facies change on hydrocarbon production. Static and dynamic modeling formed the terminal point for this integrated study of the X reservoir. Petrophysical properties that determine reservoir quality were measured. The average computed reservoir thickness, pay thickness, net pay thickness, net-to-gross (NTG), porosity and water saturation for the E1000X (Reservoir Name) reservoir zone was 114.4m, 55.4m, 42.6m, 74%, 21%and 25% respectively with no significant variation. The original hydrocarbon-in-place of the reservoir was also evaluated base on mean weighted averages of porosity, water saturation, and gross rock volumes and net-to-gross ratios. Fluid types was used to define the reservoir on the basis of neutron/density log signatures which may be basically water, oil and gas. Stratigraphic model was built and correlation panel generated. This in-turn was used to delineate the facies types across the interpreted X reservoir. The output from the facies using an acceptable global flow zone indicator (FZI) was used to model the permeability from the petrophysical analysis. Also static model was built where surfaces from seismic interpreted model was used to build a static model in other to generate geological parameters for the dynamic model simulation. In the dynamic model phase of this study, it was observed that wells placed in the channel dominated facies had better oil production performance followed by wells placed in the Shorface facies environment and least by wells placed in heterolitics environment. The prediction phase of the six wells within the 20 years period in the E1000X reservoirs shows that channels and Shoreface dominated facies gives better production performance over the production life of the wells.

Niger Delta stratigraphy, petrophysical property, static and dynamic model, facies environment