Lawrence Berkeley National Laboratory

This study investigates the effects of uncertainty in rockphysics models on estimates of reservoir parameters from joint inversion of seismic AVA and CSEM data. The reservoir parameters are related to electrical resistivity using Archie's law, and to seismic velocity and density using the Xu-White model. To account for errors in the rock-physics models, we use two methods to handle uncertainty: (1) the model outputs are random functions with modes or means given by the model predictions, and (2) the parameters of the models are themselves random variables. Using a stochastic framework and Markov Chain Monte Carlo methods, we obtain estimates of reservoir parameters as well as of the uncertainty in the estimates. Synthetic case studies show that uncertainties in both rock-physics models and their associated parameters can have significant effects on estimates of reservoir parameters. Our method provides a means of quantifying how the uncertainty in the estimated reservoir parameters increases with increasing uncertainty in the rock-physics model and in the model parameters. We find that in the example we present, the estimation of water saturation is relatively less affected than is the estimation of clay content and porosity.