A Methodology to Assimilate Seismic Data in Addition to Production Data on Real Field Applications Using the Ensemble Kalman Filter

This paper consider the use of the ensemble Kalman filter (EnKF) for estimating static and dynamic model variables on real field applications, where 3D seismic data and time-lapse seismic data in addition to production data are assimilated. The main objective of this paper is to outline the methodology and discuss different challenges in the data assimilation procedure when seismic data are introduced in the EnKF method. The presented results illustrate the benefit and the challenging issues of incorporating seismic data in the EnKF analysis.