Application of a Markov Chain Monte Carlo-AVA Inversion Algorithm for Reservoir Characterization in Offshore Nile Delta

Abstract

We propose a formulation of Amplitude Versus Angle (AVA) inversion in terms of a Markov Chain Monte Carlo (MCMC) algorithm, and we show its application for reservoir characterization and litho-fluid facies prediction in a gas-saturated reservoir in offshore Nile Delta. A linear empirical rock physics model is used to link the petrophysical characteristics (porosity, water saturation and shaliness) to the elastic attributes (P-wave velocity, S-wave velocity and density), whereas the non-linear exact Zoeppritz equations are used to relate such elastic properties to the observed AVA responses. The exact Zoeppritz equations allow us to take advantage of the long offset seismic acquisition and thus to consider a wide range of incidence angles (between 0 and 60 degrees) in the inversion. The proposed algorithm, at the expense of a relatively high computational cost, reliably estimates the posterior probability distributions of the sought parameters, taking into consideration the uncertainties in the prior information, the uncertainties in the estimated rock-physics model and the errors affecting the observed AVA responses. The match between the predicted properties and the well log information demonstrates the applicability of the proposed method and the reliability of the results.