Local and continuous updating of facies proportions for history-matching

Perturbing facies proportions can provide significant flexibility to assisted history-matching processes since facies strongly impact fluid dynamics. In this paper, we develop a new parameterization technique for varying facies proportions and matching dynamic data. It involves both the definition of proportion ratios and co-kriging estimations. This method allows for changing facies proportions over all or part of the reservoir model while other parameterization techniques can still be applied to modify heterogeneity distribution. It is also appropriate whatever the technique used to generate the facies realizations, which populate the reservoir model. Overall, it takes advantage of the two following features: it induces continuous variations in facies proportions and it allows for driving these variations from a reduced number of parameters. Therefore, this method is well-suited for history-matching: an optimization algorithm is used to modify uncertain parameters until the numerical responses simulated for this parameter set reproduce the reference production data. Last, a numerical application is presented, which stresses the potential of the proposed parameterization technique for varying facies proportions when performing history-matching.