Integrated Reservoir Characterization: a Case Study of an Onshore Reservoir in Niger Delta Basin
Reservoir characterization has long been identified as the ultimate process employed in detailed description of a reservoir in order to properly book the reserve and also to optimally place the wells and drain the reservoir. This report details the workflow of reservoir „X‟ study, right from 3D seismic interpretation to delivery of a 3D static model of the reservoir by fully integrating all the available data in the field: 3D seismic data, well logs, deviation data, core data, checkshot data, PVT data, and production data The field of study is located in the Northern Depobelt of the Niger Delta basin in the Gulf of Guinea. 21 wells have been drilled to date, penetrating 7 hydrocarbon-bearing sands (6 oils and 1 gas) between 5900 and 8500 ftss. The field was discovered by well-1 in 1965. 4 of the 21 wells were completed on this reservoir. Reservoir „X‟ is one of the 7 hydrocarbon-bearing sands in the field and has never been fully studied, that is, it does not have a static model and thus necessitated this research. The objectives of this research were to properly characterize this reservoir by integrating all the available data in the field; produce a high resolution static model of the reservoir; and re-evaluate the reserve using the 3D model. Fault and Horizon interpretations were done using Petrel (A Schlumberger software) which culminated in delivery of a 3D structural map of the reservoir. Sequence stratigraphic analyses were done using both seismic and well data to delineate the system tracts the reservoir belongs. Facies modelling and well correlation were done in Petrel to properly delineate the reservoir. Petrophysical parameters were evaluated using Techlog® (a Schlumberger software). Structural, stratigraphic and Petrophysical models were then integrated to produce a high resolution geological model (3D static model). The generated 3D static model was used to rebook the reserve of Reservoir X. Both deterministic and stochastic volumes were estimated for the reservoir. Volume (Bulk volume, net volume, Hydrocarbon Pore volume, STOIIP, Recoverable reserves etc) calculations were also done in Petrel. Structural and stratigraphic analyses revealed that the reservoir is a rollover anticline with dip closure and fault boundary. It belongs to a prograding clastic sequence of transitional marine origin. The reservoir rock properties are generally fair to good; the fluid properties and the performance plot typed the reservoir as an undersaturated reservoir with an active water drive. Uncertainty analyses showed the Stochastic most likely STOIIP, UR and reserve as 34.76MMSTB, 24.33MMSTB, and 4.33MMSTB respectively having produced 20MMSTB circa from the reservoir. Conclusively, integration of subsurface data led to building of a consistent 3-D static model of the reservoir which can be used as input into a reservoir simulation model and provides a basis for a very effective reservoir management strategy. Well prognosis was better done using the 3D model (which considers both structure and property) as against prognosis in 2D, map that onlyconig considers structure. This clearly underscores the superiority of a 3D model to a 2D map and showcases the significance of reservoir characterization.