The Application of Stochastic Inversion to Improve the Reservoir Characterization Process

In order to properly accomplish the reservoir characterization process is necessary integrating all available information about the field in a consistent model. It is not an easy task to perform this integration in practice, for which is necessary to use some specific methods such as seismic inversion. By means of seismic inversion is possible to integrate efficiently both well-log and seismic data, obtaining a model that could be used in a forecasting process. The seismic inversion can be achieved by several methods, which can be divided in two main groups: the deterministic ones and the stochastic methods. In this work we show how stochastic inversion can improve the reservoir characterization process, by comparing its results with those obtained by deterministic inversion. As a matter of fact, the stochastic inversion can use a high sample rate that is close to the cell size of reservoir models, implying that a more reliable model is generated. As additional benefits the stochastic method can generate some basic statistics measurements that improve interpretations and also, due the great number of realizations generated during the process, it is possible to perform an uncertainty study on the reservoir model.