Study On Assimilating Dynamic Data And Seismic Data Using The Ensemble Kalman Filter

As the oil field enters in the mid and later period in our country, it becomes more and more difficult to enhance oil recovery efficiency. At present, we make a large scale of 3D seismic measurements with high precision for further studying the reservoir heterogeneity. Therefore, how to combine the duplicate seismic observation data and the dynamic data to further characterize the reservoir is becoming more important now.On the basis of previous studies, I research that the Ensemble Kalman Filter is studied to integrate seismic data and dynamic data for updating reservoir properties. Reservoir static model is an important part of reservoir characterization. In general, based on conditioned data and with a priori information, the properties at unsampled locations can be estimated. However, this process is not able to ensure the reproduction of observed data including production actual seismic data. The Ensemble Kalman Filter can invert the state vector of the system model through the observation data, and minimize the difference between observation data and modeled data. In this study, random pilot-point method is used to optimize the initial model. Then, we will introduce the application of Ensemble Kalman Filter on updating reservoir static parameters. According to the application conditions of the Ensemble Kalman, we introduce the basic principles of integration of dynamic data and 3D seismic data using the Ensemble Kalman Filter. Through examples, we can see the validity of the Ensemble Kalman Filter in the integration of dynamic data and 3D seismic data, which realize a better characterization of the reservoir heterogeneity, and a better consistency with 3D seismic data. Also we campared the model updating using 3D seismic data and 4D seismic data. Using the EnKF method to integrate seismic data and dynamic data to describe reservoir characteristics, it fits observed data well, and obtains a better model. In this work, the synthetic study shows the accuracy and validity of this method.