DI21A-2598
Applicability of the Multiple-event Stacking Technique for Shear-wave Splitting Analysis

Tuesday, 15 December 2015
Poster Hall (Moscone South)
Fansheng Kong, Stephen S Gao and Kelly Hong Liu, Missouri University of Science and Technology, Rolla, MO, United States
Abstract:
For several decades, shear wave splitting (SWS) parameters (fast polarization orientations and splitting times) have been widely measured to reveal the orientation and strength of mantle anisotropy. One of the most popularly used techniques for obtaining station averaged SWS parameters is the multiple-event stacking technique (MES). Results from previous studies suggest that the splitting times obtained using MES are frequently smaller than those derived from simple averaging of splitting times obtained using the event-specific technique of Silver and Chan (1991) (SC). To confirm such apparent discrepancies between the two popularly used methods and to explore the causes, we conduct numerical experiments using both synthetic and observed data. The results show that when the anisotropic structure can be represented by a horizontal single layer of anisotropy with constant or spatially varying splitting times, MES can accurately retrieve the splitting parameters. However, when the fast orientations or both splitting parameters vary azimuthally due to lateral heterogeneities or double-layer anisotropy, the station averaged fast orientations from MES and SC are mostly comparable, but the splitting times obtained using MES are underestimated. For laterally varying fast orientations in the vicinity of a station, the magnitude of the underestimation is dependent on the arriving azimuth of the events participated in the stacking; for two-layer models of anisotropy, the resulting splitting parameters using MES are biased towards those of the top layer, due to the dominance of events with a back azimuth parallel or orthogonal to the fast orientation of the lower layer. Obviously, MES can still be applied in areas with complex or spatially varying anisotropy to obtain reliable results by stacking events from narrow back-azimuthal windows, especially when limited amounts of high-quality data are present.