Using the Ensemble Kalman Filter with 4D Data to Estimate Properties and Lithology of Reservoir Rocks

Improvement of the seismic reservoir characterisation is performed by introducing an uncertainty connected to parameters in the rock physics model. Traditionally the Ensemble Kalman filter (EnKF) method has been used to estimate permeability and porosity.<br><br>In this paper we show that when seismic difference data are available also the lithology can be estimated, which is coupled to the effective bulk modulus via the rock physics model. Incorporation of inverted seismic difference data in the EnKF introduces a large amount of data in the assimilation step. Thus, to improve the results a methodology based on a combination of a global and a local analysis scheme is proposed. The global and the local analysis are used to assimilate respectively the production data and the inverted seismic difference data, where the local scheme assume that only seismic data within a certain distance from a state variable will impact the analysis in this state variable. The technique is applied to synthetic 2D and 3D reservoir models, where effects of using local versus global analysis schemes on different inverted seismic difference data, such as acoustic impedance and Poisson's ratio, are investigated. Other evaluated factors are the effects of using an incorrect seismic data error model in the analysis schemes.