基于迭代集合卡尔曼平滑的地震波形反演

M. Gineste, J. Eidsvik, Y. Zheng
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引用次数: 1

摘要

在贝叶斯框架中考虑地震反演问题,并采用顺序滤波方法对弹性参数进行反演。该方法采用迭代集合平滑器估计地下参数,并从集合中提取估计的不确定性。对整个数据记录分区的顺序过滤条件,以自上而下的方式驱动估计过程,并使反演过程规范化。以一维介质的地震炮点记录为例,介绍了该方法。
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Seismic Waveform Inversion Using an Iterative Ensemble Kalman Smoother
Summary The seismic inverse problem is considered in a Bayesian framework and uses a sequential filtering approach to invert for elastic parameters. The method employs an iterative ensemble smoother to estimate the subsurface parameters and from the ensemble, an estimation uncertainty can be extracted. The sequential filtering conditions over partitions of the entire data record in order to drive the estimation process in a top-down manner and regularize the inversion process. The method is presented with a synthetic example using seismic shot record for a 1D medium.
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