Thomas Samuel Hudson, Joseph Asplet, Andrew M Walker
{"title":"Automated shear-wave splitting analysis for single- and multi- layer anisotropic media","authors":"Thomas Samuel Hudson, Joseph Asplet, Andrew M Walker","doi":"10.26443/seismica.v2i2.1031","DOIUrl":null,"url":null,"abstract":"Shear-wave velocity anisotropy is present throughout the earth. The strength and orientation of anisotropy can be observed by shear-wave splitting (birefringence) accumulated between earthquake sources and receivers. Seismic deployments are getting ever larger, increasing the number of earthquakes detected and the number of source-receiver pairs. Here, we present a new Python software package, SWSPy, that fully automates shear-wave splitting analysis, useful for large datasets. The software is written in Python, so it can be easily integrated into existing workflows. Furthermore, seismic anisotropy studies typically make a single-layer approximation, but in this work we describe a new method for measuring anisotropy for multi-layered media, which is also implemented. We demonstrate the performance of SWSPy for a range of geological settings, from glaciers to Earth's mantle. We show how the package facilitates interpretation of an extensive dataset at a volcano, and how the new multi-layer method performs on synthetic and real-world data. The automated nature of SWSPy and the discrimination of multi-layer anisotropy will improve the quantification of seismic anisotropy, especially for tomographic applications. The method is also relevant for removing anisotropic effects, important for applications including full-waveform inversion and moment magnitude analysis.","PeriodicalId":498743,"journal":{"name":"Seismica","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Seismica","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26443/seismica.v2i2.1031","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Shear-wave velocity anisotropy is present throughout the earth. The strength and orientation of anisotropy can be observed by shear-wave splitting (birefringence) accumulated between earthquake sources and receivers. Seismic deployments are getting ever larger, increasing the number of earthquakes detected and the number of source-receiver pairs. Here, we present a new Python software package, SWSPy, that fully automates shear-wave splitting analysis, useful for large datasets. The software is written in Python, so it can be easily integrated into existing workflows. Furthermore, seismic anisotropy studies typically make a single-layer approximation, but in this work we describe a new method for measuring anisotropy for multi-layered media, which is also implemented. We demonstrate the performance of SWSPy for a range of geological settings, from glaciers to Earth's mantle. We show how the package facilitates interpretation of an extensive dataset at a volcano, and how the new multi-layer method performs on synthetic and real-world data. The automated nature of SWSPy and the discrimination of multi-layer anisotropy will improve the quantification of seismic anisotropy, especially for tomographic applications. The method is also relevant for removing anisotropic effects, important for applications including full-waveform inversion and moment magnitude analysis.