摘要
Studies of converted S-wave data recorded on the ocean bottom seismometer(OBS)allow for the estimation of crustal S-wave velocity,from which is further derived the Vp/Vs ratio to constrain the crustal lithology and geophysical properties.Constructing a precise S-wave velocity model is important for deep structural research,and inversion of converted S-waves provides a potential solution.However,the inversion of the converted S-wave remains a weakness because of the complexity of the seismic ray path and the inconsistent conversion interface.In this study,we introduced two travel time correction methods for the S-wave velocity inversion and imaged different S-wave velocity structures in accordance with the corresponding corrected S-wave phases using seismic data of profile EW6 in the northeastern South China Sea(SCS).The two inversion models show a similar trend in velocities,and the velocity difference is<0.15 km/s(mostly in the range of 0–0.1 km/s),indicating the accuracy of the two travel time correction methods and the reliability of the inversion results.According to simulations of seismic ray tracing based on different models,the velocity of sediments is the primary influencing factor in ray tracing for S-wave phases.If the sedimentary layer has high velocities,the near offset crustal S-wave refractions cannot be traced.In contrast,the ray tracing of Moho S-wave reflections was not significantly impacted by the velocity of the sediments.The two travel time correction methods have their own advantages,and the application of different approaches is based on additional requirements.These works provide an important reference for future improvements in converted S-wave research.
基金
The National Natural Science Foundation of China under contract Nos 42276062 and 42006071
the Seismological Research Foundation for Youths of Guangdong Earthquake Agency under contract No.GDDZY202307
the Strategic Priority Research Program of Chinese Academy of Sciences under contract No.XDA22020303
the Science and Technology Planning Project of Guangdong Province-Guangdong Collaborative Innovation Center for Earthquake Prevention and Disaster Mitigation Technology under contract No.2018B020207011.