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Seismic anisotropy reveals that seismic wave velocity, amplitude, and other physical properties show variations in different directions, which can be divided into lattice preferred orientation (LPO) and shape preferred orientation (SPO) according to its physical mechanisms. The main methods for studying seismic anisotropy include shear-wave splitting analysis, P-wave travel time inversion and surface-wave tomography, etc. There are some differences and correlations among these methods. Seismic anisotropy is an important way to reveal the dynamic processes of crust-mantle evolution, and it is significant to monitor crustal stress changes and improve seismic exploration studies. With the help of long-term observation, the application of machine learning techniques and combining inversion based on multiple phases would become the potential developments in seismic anisotropy studies. This may improve the understanding of complex seismic anisotropic model, such as multiple layers anisotropy with oblique axis of symmetry.
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Zhao et al. (2024) studied this question.
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