Summary We propose a two tiered inversion strategy that aims to address and better explore the solution space during seismic inversion and reservoir characterization. First a range of plausible geological prior scenarios are defined in terms of layer configurations and horizon/picking uncertainty, number of facies and their corresponding abundances, and rock property trends and relationships (with associated uncertainties). Then, per scenario, stochastic Markov chain Monte Carlo sampling (McMC) is performed to create equiprobable realizations from the posterior distribution. The benefit of this approach is twofold; first of all, no prior low frequency model is stipulated by the operator, with the low frequency content instead being derived through iterative fitting of seismic amplitude data via sampling from facies based elastic property trends. This provides a novel way of exploring uncertainty in the low frequency end of the earth spectrum.