3D Least-squares Migration of Receiver Function

Receiver function (RF) imaging is a crucial method that employs converted teleseismic waves to characterize discontinuities in the Earth's interior. The proliferation of dense areal seismic arrays has necessitated developing advanced imaging techniques to effectively utilize the increasing seismic data. In this study, we develop a 3D regularized least-squares migration (LSM) method for RF imaging, which allows for imaging subsurface structures using teleseismic waves incident from arbitrary directions. We employ the Split-step Fourier algorithm to solve the acoustic wave equation, resulting in the construction of forward and adjoint operators for wavefield propagation. These operators facilitate the transformation of the seismic migration into an inverse problem in a least-squares sense, which enables suppressing the strong acquisition footprints and compensating for inadequate illumination. Tikhonov regularization is performed to generate preconditioned images with higher resolution than standard migration algorithms. To assess the performance of the proposed method, we conduct synthetic experiments by simulating teleseismic recordings using the SPECFEM3D code. The input model incorporates undulated and step Moho interfaces. The obtained migration images demonstrate that the capability of the developed LSM method to accurately recovers the 3D geometry of the Moho interfaces. The current study only considers the P-to-S converted waves, and future research will focus on utilizing free-surface multiples to obtain higher-resolution subsurface structures.