Polargui: A matlab-based tool for polarization analysis of the three-component seismic data using different algorithms

Huailiang Li, Kai Qu, Wenzheng Rong, Xianguo Tuo, Jing Lu, Ruili Wang, Xuben Wang, Jérémie Courtois

Research output: Journal PublicationArticlepeer-review

4 Citations (Scopus)

Abstract

We present an open-source and MATLAB-based tool with an easy-to-use graphical user interface (GUI) consisting of four polarization analysis approaches: The particle-motion trajectory (a hodogram in a 3D plane), eigenvalue decomposition (EVD) based on the covariance matrix (including two calculation methods), singular value decomposition using principal component analysis, and EVD based on a constructed analytic signal matrix (EVD-ASM). We review the calculation processes and features of the four cited methods. The eigenvalue and eigenvector are applied to obtain the polarization attributes of the three-component (3C) seismic data. Using rose graphs and histograms, the corresponding azimuth and incidence angle are calculated to determine the propagation direction of the seismic wave. Statistical distribution curves of the corresponding rectilinearity and planarity of the waves are also plotted. The polarization analysis GUI can simultaneously analyze two selected data sections in a seismic recording corresponding to P and S waves. We evaluate the performance of these algorithms using real 3C earthquake datasets. Comparison tests indicate that the aforementioned four methods have different time consumption, and the differences between the results of the EVD-ASM and those of the other methods are very small.

Original languageEnglish
Pages (from-to)3821-3831
Number of pages11
JournalSeismological Research Letters
Volume92
Issue number6
DOIs
Publication statusPublished - Nov 2021
Externally publishedYes

ASJC Scopus subject areas

  • Geophysics

Fingerprint

Dive into the research topics of 'Polargui: A matlab-based tool for polarization analysis of the three-component seismic data using different algorithms'. Together they form a unique fingerprint.

Cite this