Bayesian ISOLA: new tool for automated centroid moment tensor inversion

Abstract

We have developed a new, fully automated tool for the centroid moment tensor (CMT) inversion in a Bayesian framework. It includes automated data retrieval, data selection where station components with various instrumental disturbances are rejected and full-waveform inversion in a space-time grid around a provided hypocentre. A data covariance matrix calculated from pre-event noise yields an automated weighting of the station recordings according to their noise levels and also serves as an automated frequency filter suppressing noisy frequency ranges. The method is tested on synthetic and observed data. It is applied on a data set from the Swiss seismic network and the results are compared with the existing high-quality MT catalogue. The software package programmed in Python is designed to be as versatile as possible in order to be applicable in various networks ranging from local to regional. The method can be applied either to the everyday network data flow, or to process large pre-existing earthquake catalogues and data sets.

Nucleation Phase and Dynamic Inversion of the Mw 6.9 Valparaíso 2017 Earthquake in Central Chile

“…We inverted the full moment tensor for each identified earthquakes using the ISOLA code (Sokos & Zaharadnik, ; Vackář et al, ). We explored for the centroid and the best fitting nondouble couple using a 1 km width (50 m step) grid search around the hypocenter.…”

Hamiltonian Monte Carlo Inversion of Seismic Sources in Complex Media

“…With the focus of this work being on Hamiltonian Monte Carlo as a method for source inversion, we admittedly paid less attention to other aspects of the problem that may not be less important. These include the quantification of forward modeling and observational uncertainties, as performed, for instance, by Mustać and Tkalčić (), Silwal and Tape (), Staehler and Sigloch (, ), Vackár et al (), and Wéber ().…”

Bayesian inference and interpretation of centroid moment tensors of the 2016 Kumamoto earthquake sequence, Kyushu, Japan

“…We apply modification of the Bayesian full-waveform CMT inversion, ISOLA-ObsPy (Vackář et al 2017), which allows for reliable assessment of the solution uncertainty. In this method, a regular grid of four nonlinear CMT model parameters (location ξ and time τ) is considered.…”

“…(3) can be obtained by integration over all the ten CMT parameters. In our case, we integrate over the space-time grid points (Vackář et al 2017), where the term dV i is the product of grid steps of all the four nonlinear model parameters (i.e., the space and time discretization steps). The value a i is an integral of PDF i at the given space-time grid point.…”

“…It thus carries information about the quality of the least squares solution in particular grid point. Vackář et al (2017) propose to inspect posterior PDF of any CMT parameters by generating set of random possible solutions from the total ten-dimensional posterior PDF. This can be achieved by drawing a i random samples at each space-time grid point from the multivariate normal distribution specified by m i and C M i .…”