Multiscale geostatistical history matching using block direct sequential simulation

This paper proposed a multiscale geostatistical history matching methodology using a new algorithm. The challenge of this work is the development and the application of an algorithm that couples different geological scales by recurring to Block Direct Sequential Simulation. In order to speed-up the history matching procedure we first optimize the reservoir model at a very coarse grid which is then used as an auxiliary model to perform the history matching at a very fine scale. With the development of this workflow is expected a better coarse and fine solution, an improved and more reliable reservoir model with a significant reduction of computing time and with a good integration of dynamic data in the static model. We show this novel approach in a challenging synthetic case study based on a fluvial environment.