EnKF整合三维地震数据和动态数据的应用

Application of assimilating 3-D seismic data with dynamic data using ensemble Kalman filter

主要介绍集合卡尔曼滤波EnKF在更新油藏储层静态参数方面的应用。根据集合卡尔曼滤波产生的必要条件,介绍了集合卡尔曼滤波整合动态数据和三维地震数据的基本原理。通过实例分析,验证了集合卡尔曼滤波在整合动态数据和三维地震数据更新油藏参数方面的有效性,更新后的油藏模型能够较好地反映储层非均质性,并且与三维地震数据有较好的一致性。还比较了利用三维地震数据和四维地震数据进行更新油藏模型的差别。通过EnKF方法将地震数据和动态数据结合起来描述油藏特征,能够很好地拟合观测数据,并获得较好的模型。

Ensemble Kalman filter(EnKF) was used to update static reservoir properties.Starting from the necessary conditions of EnKF,this paper described the mathematical principles of assimilating 3-D seismic data and dynamic data using EnKF.The proposed method was validated using a synthetic data.Results show that the heterogeneity of reservoir can be manifested by the assimilated data.We also compared the reservoir models updated using 3-D and 4-D seismic data.A better reservoir model was resulted from assimilating 3-D seismic data and dynamic data using EnKF.