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Joint Inversion of Facies and Reservoir Properties
- Publisher: European Association of Geoscientists & Engineers
- Source: Conference Proceedings, 81st EAGE Conference and Exhibition 2019, Jun 2019, Volume 2019, p.1 - 5
Abstract
We present a Bayesian inversion methodology for seismic reservoir characterization studies. The goal of the method is to predict rock and fluid properties and facies given a set of seismic data or amplitudes and their posterior probability distribution. The joint distribution of facies and petrophysical properties is modelled using a mixture of non-parametric distributions. This assumption does not require any particular shape of the probability density function and allows modelling the non-Gaussian and non-unimodal behaviour of rock and fluid properties caused by the presence of different litho-fluid classes and the non-linear relations between model properties and measured data. The method provides the posterior distribution of facies and reservoir properties, the most-likely models and their associated uncertainty, and it is successfully applied to synthetic and real data.