Integrated 3-Dimensional Modeling of Igloo R3 Reservoir, Onshore Niger Delta, Nigeria
Anakwuba, Emmanuel K.; Onwuemesi, Godwin A.; Onyekwelu, Clement U.; Chinwuko, Ifeanyi A.; Akachikelu, Ndubuisi; Obiadi, Izuchukwu I.
3-dimensional static model of R3 reservoir in Igloo Field, Onshore Niger Delta has been constructed by integrating 3-D seismic volume, geophysical well logs and core petrophysical data. The model utilizes a combined petrophysical-based reservoir zonation and geostatistical inversion of seismic attributes to reduce vertical up scaling problems and improve the estimation of reservoir properties between wells. The reservoir structural framework was interpreted to consist of 3 major synthetic faults; two of them formed northern and southern boundaries of the field while the other separated the field into two hydrocarbon compartments. Both compartments were pillar gridded into 39396 cells using a 50 x 50 m dimension over an area of 48 square kilometers. Analysis of the field petrophysical distribution showed an average of 21% porosity, 34% Volume of Shale and 350 mD permeability. Eleven flow units delineated from Stratigraphic Modified Lorenz (SML) plot were used to define the reservoir's stratigraphic framework. The calibration of acoustic impedance using sonic and density logs porosity showed a 0.88 correlation co-efficient; this formed the basis for geostatistical seismic inversion process. Acoustic impedance was transformed into reservoir parameters using Sequential Gaussian Simulation (SGS) algorithm with collocated co-kriging and variogram models. Ten equiprobable acoustic impedance models were generated and further converted into porosity models by utilizing their bivariate relationship. Permeability was modeled with a single transform of core porosity with correlation coefficient of 0.86. A conventional model of porosity was compared with the product of this study and the result showed differences in their spatial distribution which is a major control to fluid flow. However, there were similarities in their probability distribution function (PDF) and cumulative distribution function (CDF).
AAPG Search and Discovery Article #90163©2013AAPG 2013 Annual Convention and Exhibition, Pittsburgh, Pennsylvania, May 19-22, 2013