A review of inverse methods in seismic site characterization

Abstract

Seismic site characterization attempts to quantify seismic wave behavior at a specific location based on near-surface geophysical properties, for the purpose of mitigating damage caused by earthquakes. In recent years, techniques for estimating near-surface properties for site characterization using geophysical observations recorded at the surface have become an increasingly popular alternative to invasive methods. These observations include surface-wave phenomenology such as dispersion (velocity-frequency relationship) as well as, more recently, full seismic waveforms. Models of near-surface geophysical properties are estimated from these data via inversion, such that they reproduce the observed seismic observations. A wide range of inverse problems have been considered in site characterization, applying a variety of mathematical techniques for estimating the inverse solution. These problems vary with respect to seismic data type, algorithmic complexity, computational expense, physical dimension, and the ability to quantitatively estimate the uncertainty in the inverse solution. This paper presents a review of the common inversion strategies applied in seismic site characterization studies, with a focus on associated advantages/disadvantages as well as recent advancements.

Introduction to the special issue of the Consortium of Organizations for Strong Motion Observation Systems (COSMOS) international guidelines for applying noninvasive geophysical techniques to characterize seismic site conditions

“…To this end, eleven papers were curated by the COSMOS guest editors. These articles are assigned to three main themes: the first topic articulates the best practice for applications of various site characterization methods (Louie et al 2022;Pancha and Apperley 2022;Hayashi et al 2022;Hunter et al 2022;Molnar et al 2022;Stephenson et al 2022); the second is agnostic to the aforementioned techniques and focuses on processing and analyzing data (Toro 2022;Vantassel and Cox 2022), including one paper on the role of analysts (Asten et al 2022); and the third involves reviews of select topics that are fundamental for consideration in all techniques (Gosselin et al 2022;Parolai et al 2022). All papers are aligned on issues relating to uncertainty, which are paramount to the practice of site characterization as performed at the time of publication.…”

From ambient vibration data analysis to 1D ground-motion prediction of the Mj 5.9 and the Mj 6.5 Kumamoto earthquakes in the Kumamoto alluvial plain, Japan.

“…Several approaches were proposed as well for the inversion of DC data to obtain the Vs pro le at the investigated site (Herrmann 1987;Yamanaka and Ishida 1996;Wathelet 2008). This last step of analysis is characterized by high non-linearity and non-uniqueness of the solution (Foti et al 2009;Renalier et al 2010;Boaga et al 2011;Di Giulio et al 2012, Gosselin et al 2022) which affects the output of a ground response analysis (GRA). The signi cant expertise required by passive surface wave methods promoted the development of projects and international initiatives devoted to the advancement of the current state-of-practice (Bard et al 2010;Garofalo et al 2016a, b).…”