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地震记录卡尔曼估计存在先验信息的不确定性问题,地震记录的独立变量分析的分解分量可以给出卡尔曼估计诸分量更全面的先验信息.独立变量分析迭代逼近输出相互独立的变量,存在源信息独立分量不准确问题,利用卡尔曼估计理论,优化逼近可以减小这种不准确性.考虑两种理论方法的优缺点,把独立分量分析理论和卡尔曼最优估计理论结合起来,研究基于卡尔曼最优估计地震反射系数独立变量分解提取方法.对地震数据进行独立变量分解,得到初始分解分量,对各分量和地震记录建立卡尔曼估计状态方程,根据建立的方程,利用递推寻优过程进行分量的最佳估计,考虑到地震记录的横向相关信息,增加有用信号横向相关信息约束.理论模型和实际资料验证了方法的正确可靠性及应用效果.
Seismic Kellman’s estimation has the problem of uncertainty of a priori information, and the decomposed components of independent variable analysis of seismic records can give more comprehensive prior information about the components of Kalman estimation. Independent variable analysis iterative approximation outputs independent variables, There is a problem of inaccurate independent components of source information, and Kalman estimation theory and optimization approximation can reduce this inaccuracy.Considering the advantages and disadvantages of the two theoretical methods, combining independent component analysis theory with Kalman’s optimal estimation theory, The independent variable decomposition method based on Kalman’s optimal estimation of seismic reflection coefficient is studied.Animal variable decomposition is performed on the seismic data to obtain the initial decomposition component and the Kalman estimation equation of state is established for each component and the seismic record.According to the established equation, The optimal estimation of the components is carried out in the optimization process and the horizontal information of the useful signal is added considering the transverse related information of the seismic record.The theoretical model and the actual data verify the correctness and reliability of the method and the application effect.