Least-Squares Migration Imaging of Receiver Functions

The growth of seismic data recorded by dense arrays has stimulated the development of new array-based receiver function (RF) imaging techniques. This study examines the feasibility and performance of the least-squares migration (LSM) method, a state-of-the-art technique used in exploration seismology, to lithospheric imaging using teleseismic RFs. Taking advantage of a pair of forward (demigration) and adjoint (migration) operators, the LSM casts migration as a regularized least-squares optimization problem. We employ the split-step Fourier method to design the two operators and conduct wavefield propagation in heterogeneous media. Synthetic tests with a two-layered crustal model and varying ratio of missing traces demonstrate that LSM is capable of suppressing imaging artifacts and improving imaging resolution compared to conventional migration. Real data application is conducted using teleseismic data recorded by the Himalayan-Tibetan continental lithosphere during mountain building (Hi-CLIMB) array deployed on the Tibetan Plateau. Considering the irregular and noisy recordings from field acquisition, we adopt signal processing algorithms, including the Radon transform and singular spectrum analysis (SSA) filter, to regularize the wavefields and precondition the RFs. The proposed workflow resolves fine-scale crustal structures that are consistent with earlier studies. Overall, our study offers a new high-resolution RF imaging tool and inspires the future development of advanced array processing workflows.