Samuel Bignardi

OpenHVSR: imaging the subsurface 2D/3D elastic properties through multiple HVSR modeling and inversion

Abstract OpenHVSR is a computer program developed in the Matlab environment, designed for the simultaneous modeling and inversion of large Horizontal-to-Vertical Spectral Ratio (HVSR or H/V) datasets in order to construct 2D/3D subsurface models (topography included). The program is designed to provide a high level of interactive experience to the user and still to be of intuitive use. It implements several effective and established tools already present in the code ModelHVSR by Herak (2008) , and many novel features such as: -confidence evaluation on lateral heterogeneity -evaluation of frequency dependent single parameter impact on the misfit function -relaxation of V p / V s bounds to allow for water table inclusion -a new cost function formulation which include a slope dependent term for fast matching of peaks, which greatly enhances convergence in case of low quality HVSR curves inversion -capability for the user of editing the subsurface model at any time during the inversion and capability to test the changes before acceptance. In what follows, we shall present many features of the program and we shall show its capabilities on both simulated and real data. We aim to supply a powerful tool to the scientific and professional community capable of handling large sets of HSVR curves, to retrieve the most from their microtremor data within a reduced amount of time and allowing the experienced scientist the necessary flexibility to integrate into the model their own geological knowledge of the sites under investigation. This is especially desirable now that microtremor testing has become routinely used. After testing the code over different datasets, both simulated and real, we finally decided to make it available in an open source format. The program is available by contacting the authors.

Geometric Seismic-Wave Inversion by the Boundary Element Method

Abstract Surface‐wave methods are widely used in earth sciences and engineering for the geometric characterization of geological bodies and tectonic structures of the subsurface. These techniques exploit the dispersive nature of Rayleigh waves to indirectly estimate shear wave velocity profiles from surface‐wave measurements; however, they are limited to parallel‐layered geometries. To overcome such limitations, we present a new class of geometric inverse models for a full waveform inversion (FWI) based on the boundary element method (BEM). The proposed approach enables an effective identification of two dimensional (2D) subsurface geometries by directly estimating the shape of laterally varying interfaces from raw measurements. It thus aims at filling the gap between the standard simplistic parallel‐layered‐based inversion and that of more complex three‐dimensional (3D) geometries based on finite element methods (FEMs). Numerical tests on synthetic data unveil the effectiveness of the inverse algorithm, and its applicability to field measurements is finally presented.

Two-Dimensional Seismic Wave Modeling and Inversion by the Boundary Element Method

Surface wave methods (SWM) are widely used for the geophysical characterization of geological bodies and tectonic structures in both Earth Sciences and Engineering. SWMs exploit the dispersive nature of Rayleigh waves to indirectly estimate shear wave velocity profiles from surface wave measurements, but they are limited to parallel-layered geometries. To overcome such limitations, we exploit the Boundary Element Method (BEM) to define a new class of geometric inversion models that allows to go directly from raw measurements to estimating the shape of laterally varying soil interfaces. The proposed approach enables a robust identification of the subsurface geometry and it aims at filling the gap between the standard simplistic parallel-layered-based SWM and the more complex three-dimensional Full Wave Inversion (FWI) based on Finite Element Methods. Numerical tests on synthetic data unveil the effectiveness of the inverse algorithm and its applicability to wave measurements. An application to field data is finally presented.

OpenHVSR - Processing toolkit: Enhanced HVSR processing of distributed microtremor measurements and spatial variation of their informative content

Abstract The investigation of seismic ambient noise (microtremor) in spectral ratio form, known as the Horizontal-to-Vertical Spectral Ratio technique, is extremely popular nowadays both to investigate large areas in a reduced amount of time, and to leverage a wider choice of low cost equipment. In general, measurements at multiple locations are collected to generate multiple, individual spectral ratio curves. Recently, however, there has been an increasing interest in spatially correlating informative content from different locations. Accordingly, we introduce a new computer program, “OpenHVSR – Processing Toolkit”, developed in Matlab (R2015b), specifically engineered to enhance data processing with the purpose of spatially correlating different forms of informative data content, creation of maps, and display of the results in 2D and 3D. The interface is designed to be user friendly while tightly binding processing and visualization so that the effects of different processing choices can be immediately evaluated. Further, bedrock mapping capability, as introduced by Ibs-von Seht and Wohlenberg (1999) is included both through the computation of bedrock depth via a set of published regressions or by computing a customized regression based on the data at hand. The program aims at implementing the most effective and desirable processing tools present in other commercial and non-commercial alternatives, all in one bundle, freely available to the scientific community. In addition to incorporating and enhancing currently available state of the art tools, we have integrated several original features that are not present in any other program. The presented processing toolkit naturally integrates with our data inversion software, “OpenHVSR”, published in 2016. Together, they constitute a complete workflow for the Horizontal-to-Vertical Spectral Ratio method. We expect this first version to be of great use to researchers and hope it will constitute the basis for further collaborative development toward future releases oriented at exploring the potentials of this technique.

Surface Waves in Laterally Heterogeneous Media

AbstractSurface wave methods exploit the dispersive properties of Rayleigh and Love waves to estimate the shear wave velocity profiles in vertically heterogeneous subsurfaces. Typically, they rely on a simplified one-dimensional (1D) analytical forward model where the lateral variation of the layer thickness is neglected and so is the fraction of the incident energy of the fundamental mode that is reflected or converted to higher modes. A theoretical study is presented that attempts to define an analytical model that overcomes the limitations of 1D forward models. In particular, we revisit properties of semianalytical approaches that aim at solving the dynamics of Love waves in laterally heterogeneous media made of a soft upper layer of varying thickness lying over an infinitely deep hard layer. The novel analytical model stems from a local-mode expansion of waves with laterally varying amplitudes, which allows for both reflections of the incident modes and coupling to higher modes. The best wave approxim...