Article Vol. 22, No. 1, p. 155169, February 2018 http://dx.doi.org/10.1007/s12303-017-0018-4 pISSN 1226-4806 eISSN 1598-7477 Geosciences Journal GJ Lithology and fluid prediction from simultaneous seismic inversion over Sandfish field, Niger Delta, Nigeria Lukumon Adeoti 1 *, Oluwakemi Y. Adesanya 1 , Kayode F. Oyedele 1 , Itsemode P. Afinotan 2 , and Ayo Adekanle 2 1 Department of Geosciences, Faculty of Science, University of Lagos, Akoka, Nigeria 2 Earth Science and Reservoir Services, Chevron Nigeria Limited, 2 Chevron Drive, Lekki, Lagos, Nigeria ABSTRACT: Seismic inversion has been widely practiced in the oil and gas industry because it generates broad bandwidth of impedance data which maximizes vertical resolution and minimizes tuning effects. The lack of accurate prediction of lithology and fluid content of subtle features identified in seismic data acquired over the Sandfish field, Niger Delta, Nigeria necessitated the use of seismic inversion. In this paper, simultaneous seismic inversion is adopted to integrate seismic and well data for quantitative interpretation and uncertainty assessment of the subsurface reservoirs in the Sandfish field. Three Sandfish (Sfn) wells with the required petrophysical logs, check-shot data, high quality 3D seismic data of five angle stacks (6–12°, 12–18°, 18–26°, 26–32°, and 32– 42°) were used for the analysis. A feasibility study including cross-plots of petrophysical and elastic properties from well data was first carried out to establish rock property relationships in the interval of interest. Biot-Gassmann fluid substitution analysis was also used to reveal sensitivity of rock properties to pore-fill type. Low frequency (0–2 Hz) models were generated from interpolation of high- cut-filtered P-sonic, S-sonic, and density logs guided by interpreted seismic horizons. The low frequency models were used to broaden the spectrum to estimate elastic volumes. The five partial angle stacks were simultaneously inverted using Jason’s Rock-Trace ® inversion software which iterated trial inversions until the model sufficiently matched the seismic data. The inverted P-impedance (Z P ), S- impedance (Z S ), and density () were used to derive Poisson’s ratio (), volume of sand (Vsand), lambda-rho (), and mu-rho (). The cross-plot of  with  from well data looks similar to that from inverted results. Sands and shales are discriminated on the basis of sands having low values of  . Hydrocarbon-bearing sands are differentiated from water-bearing sands and shales on the basis of having lowest values of  . The Biot-Gassmann fluid substitution analysis at reservoir N-01 reveals typical class III amplitude variation with angle (AVA) responses for low-impedance hydrocarbon sands. The lithology and fluid prediction maps extracted from Vsand and  at the N-01 seismic horizon show variation in lithology and fluid types for the entire volume. The inversion products reveal heterogeneities in the reservoirs away from well control validated by a blind well test. Hence, the study shows that rock-property model from a simultaneous inversion is an effective predictive tool for lithology and fluid types which in turn can guide well placement and predict reservoir development in the field of study. Key words: elastic properties, simultaneous inversion, low frequency models, reservoir development, lambda-rho, mu-rho Manuscript received April 20, 2016; Manuscript accepted February 19, 2017 1. INTRODUCTION Simultaneous inversion is a sophisticated process to invert the seismic data into elastic properties of the reservoir. The estimation of spatial distribution of the elastic parameters from prestack seismic data is of interest to both exploration and reservoir geophysicists because the seismic attributes extracted from seismic data enhance information that is more subtle in a traditional seismic image, leading to a better geological and geophysical interpretation (Contreras et al., 2006). There are several approaches to invert seismic data for quantitative estimates of reservoir properties but some require prior information to constrain the inversion. The prior information may include a rock physics model and rock property trends to relate reservoir properties (Connolly and Hughes, 2014). Using broad-band seismic data will significantly reduce the bias of the initial input (Lortzer and Berkhout, 1992; Goodway et al., 1997). In the area of reservoir properties prediction, prestack data with different weights were used to generate fluid factor and pseudo- Poisson’s ratio sections to detect fluids and lithology types in *Corresponding author: Lukumon Adeoti Department of Geosciences, Faculty of Science, University of Lagos, Akoka, Nigeria Tel: +234-8034739175, E-mail: lukuade@yahoo.com The Association of Korean Geoscience Societies and Springer 2018