Developing geostatistical reservoir models that are geologically realistic and correctly reflect production history is important for accurately assessing the uncertainty associated with production forecasts. Conditioning reservoir models to dynamic data is challenging due to the non-linear relationship between the measured flow response data and the model parameters (porosity, permeability etc.). Recently, a novel methodology was presented to integrate geological as well as production information into reservoir models in a probabilistic manner (CIM paper 2002-125). In this paper we investigate the convergence aspects of the algorithm and propose an extension to account for multiple flow domains in a reservoir and locally varying deformation parameters. The improved methodology is validated on a complex reservoir model.