Super-resolution least-squares prestack Kirchhoff depth migration using the L0-norm

Super-resolution least-squares prestack Kirchhoff

depth migration using the L0-norm

Wu Shao-Jiang;Wang Yi-Bo;Ma Yue;Chang Xu

【期刊名称】《应用地球物理（英文版）》 【年(卷),期】2018(015)001

【摘要】Least-squares migration (LSM) is applied to image subsurface structures and lithology by minimizing the objective function of the observed seismic and reverse-time migration residual data of various underground

reflectivity

models.LSM

reduces

the

migration

artifacts,enhances the spatial resolution of the migrated images,and yields a more accurate subsurface reflectivity distribution than that of standard migration.The introduction of regularization constraints effectively improves the stability of the least-squares offset.The commonly used regularization terms are based on the L2-norm,which smooths the migration results,e.g.,by smearing the reflectivities,while providing

stability.However,in

exploration

geophysics,reflection

structures based on velocity and density are generally observed to be discontinuous in depth,illustrating sparse reflectance.To obtain a sparse migration profile,we propose the super-resolution least-squares Kirchhoff prestack depth migration by solving the L0-norm-constrained optimization problem.Additionally,we introduce a two-stage iterative soft and hard thresholding algorithm to retrieve the super-resolution