4D Seismic History Matching of the Norne Field Model Using Ensemble-based Methods with Distance Parameterization

Quantitative use of 4D seismic data for history matching is still challenging. This is partly because of the high dimensionality and the large uncertainty involved in the seismic data. To circumvent these difficulties there have been some methods proposed with a focus on reparameterization of seismic attributes and reformulation of seismic objective functions so that the integration of 4D seismic data is more robust and efficient. A distance parameterization of seismic anomalies due to saturation effects was previously proposed to history match reservoir models in combination with the ensemble Kalman filter (EnKF). Because the parameterization reduces both nonlinearity and the effective number of data, an improved functioning of the EnKF can be achieved. In this paper, we further improve the distance parameterization by adopting a more robust measure of the distance between observed and simulated fronts. Numerical experiments with Norne field model are presented in which improved functioning of the proposed method is demonstrated.