New Formulation of the Objective Function for Better Incorporation of 4D Seismic Data into Reservoir Models

To build consistent reservoir models, 4D seismic data are an invaluable source of information on fluid displacements and geology over extensive areas of the reservoir. In this paper, we focus on the integration of such data to improve the obtained optimal model in a history matching process. However, this is a challenging task involving a proper definition of the objective function. The objective function computes the discrepancy between observed data and responses computed by the reservoir model. Classical formulations based on the least square mismatch are not adapted to deal with complex, noisy and numerous data such as 4D inverted seismic data. In this paper, we study the integration of seismic data in order to improve the optimal model obtained by the history matching process. The main focus of this paper is to define an experimental methodology to compare and classify seismic matching methods. In particular, we propose an efficient algorithm which focuses on the main trends in a seismic cube. This new algorithm is investigated in the context of seismic data, and its potential is demonstrated on several history matching reservoir examples.