Abstract
3D seismic volume and two well logs data labelled Bonna-6 and Bonna-8 were employed in the inversion process. The data set was simultaneously inverted to produce P- and S-impedances, density, VP − VS, and PI seismic attributes. An average “c” term value of 1.37 was obtained from the inverse of the slope of the crossplot of P-impedance versus S-impedance for Bonna-6 and Bonna-8 wells. This value was employed in the inversion process to generate the PI attribute, which aided in reducing the non-uniqueness inherent in discriminating the probable reservoir sands. Five seismic attributes slices were generated to ascertain the superiority of each attribute in delineating the probable reservoir sand. These attributes were: density, S-impedance, P-impedance, VP− VS ratio and PI. These attributes reveal low value of density (1.96 − 2.14 g/cc), P-impedance (1.8 × 104 − 2.1 × 104) ft/s*g/cc, S-impedance (9.2 × 103 − 1.1 × 104) ft/s*g/cc, VP − VS (1.65 − 1.72) and PI (4.9 × 103 − 5.1 × 104) ft/s*g/cc around the area inferred to be hydrocarbon saturated reservoir. Although the attributes considered reveals the same zone suspected to be probable hydrocarbon zone, PI gives a better discrimination when compared to other attributes. A distinctive spread and demarcation of the delineated hydrocarbon sand are observed in the PI attribute slice.
Modelling and mapping hydrocarbon saturated sand reservoir using Poisson’s impedance (PI) inversion: a case study of Bonna field, Niger Delta swamp depobelt, Nigeria