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改进标准集合卡尔曼滤波方法,对非线性油藏的历史拟合及反演问题进行研究。油藏生产历史数据历史拟合过程中只对油藏模型参数进行更新,然后利用更新的模型参数从初始状态重新运行油藏数值模拟软件进行下一拟合时刻的生产预测,从而解决由于非线性引起的更新模型与更新动态场间的不一致性。利用改进方法对一个假定油藏的初始油水界面位置、渗透率场以及孔隙度场等参数进行估计,并与标准集合卡尔曼滤波方法的结果进行比较。结果表明,改进的集合卡尔曼滤波方法能得到很好的估计和预测结果。
Improve the standard set Kalman filtering method to study the history fitting and inversion of nonlinear reservoirs. Only the reservoir model parameters are updated in the history fitting process of reservoir production history. Then, the reservoir model simulation software is re-run from the initial state to make production prediction at the next fitting time by using the updated model parameters, so as to solve the problem of non- Caused by the updated model and update the dynamic field of inconsistencies. The parameters of initial oil-water interface, permeability field and porosity field of a hypothetical oil reservoir are estimated by using the improved method and compared with the results of the standard ensemble Kalman filter. The results show that the improved ensemble Kalman filter method can get good estimation and prediction results.