Seismic driven reservoir characterization, offshore Niger Delta, Nigeria

This paper presents the subsurface characterization by applying integrated three dimensional seismic attributes analysis on a 3D seismic dataset from OPO field, within the western Niger Delta basin. The volume attributes aimed at extracting features associated with hydrocarbon presence detection, net pay evaluation and porosity estimation for optima reservoir characterization. Neural network (NN) derived chimney properties prediction attribute was used to evaluate the integrity of the delineated structural traps. Common contour binning was employed for hydrocarbon prospect evaluation, while the Seismic coloured inversion was also applied for net pay evaluation. Amplitude anomalies were used to delineate bright spots and flat spots; good reservoirs in term of their porosity models, and fluid content and contacts (GOC & OWC) were identified in the area through common contour binning, seismic colour inversion and supervised NN classification