Abstract：Regularization of irregular spaced seismic data is a crucial step of data processing.In this paper,a data regularization method based on iteratively re-weighted least-squares inversion is proposed,which can eliminate the effect of burst noise on the interpolated data.The weighting operator is introduced to weight the data fit residual under Cauchy norm.Local slope field estimated by plane wave destructor is used as prior information to make the process of inversion stable and interpolate the aliased data correctly.The inverse problem is solved by the preconditioning conjugate gradient method with fast convergence.Parallel processing along time slices for three dimensional data cube can promote the efficiency of three dimensional data regularization further.Experimental results on theoretical model and real seismic data show that the proposed method is fast,efficient and applicable.
刘玉金, 李振春. 局部平面波模型约束下的迭代加权最小二乘反演三维地震数据规则化[J]. 石油地球物理勘探, 2012, 47(3): 418-424.
Liu Yujin, Li Zhenchun. Three dimensional data regularization by iteratively re-weighted least-squares inversion based on the local plane wave model. OGP, 2012, 47(3): 418-424.
