Reconstruction, with tunable sparsity levels, of shear wave velocity profiles from surface wave data
(2021) In Geophysical Journal International 225(3). p.1935-1951- Abstract
The analysis of surface wave dispersion curves is a way to infer the vertical distribution of shear wave velocity. The range of applicability is extremely wide: going, for example, from seismological studies to geotechnical characterizations and exploration geophysics. However, the inversion of the dispersion curves is severely ill-posed and only limited efforts have been put in the development of effective regularization strategies. In particular, relatively simple smoothing regularization terms are commonly used, even when this is in contrast with the expected features of the investigated targets. To tackle this problem, stochastic approaches can be utilized, but they are too computationally expensive to be practical, at least, in... (More)
The analysis of surface wave dispersion curves is a way to infer the vertical distribution of shear wave velocity. The range of applicability is extremely wide: going, for example, from seismological studies to geotechnical characterizations and exploration geophysics. However, the inversion of the dispersion curves is severely ill-posed and only limited efforts have been put in the development of effective regularization strategies. In particular, relatively simple smoothing regularization terms are commonly used, even when this is in contrast with the expected features of the investigated targets. To tackle this problem, stochastic approaches can be utilized, but they are too computationally expensive to be practical, at least, in case of large surveys. Instead, within a deterministic framework, we evaluate the applicability of a regularizer capable of providing reconstructions characterized by tunable levels of sparsity. This adjustable stabilizer is based on the minimum support regularization, applied before on other kinds of geophysical measurements, but never on surface wave data. We demonstrate the effectiveness of this stabilizer on (i) two benchmark—publicly available—data sets at crustal and near-surface scales and (ii) an experimental data set collected on a well-characterized site. In addition, we discuss a possible strategy for the estimation of the depth of investigation. This strategy relies on the integrated sensitivity kernel used for the inversion and calculated for each individual propagation mode. Moreover, we discuss the reliability, and possible caveats, of the direct interpretation of this particular estimation of the depth of investigation, especially in the presence of sharp boundary reconstructions.
(Less)
- author
- Vignoli, Giulio ; Guillemoteau, Julien ; Barreto, Jeniffer and Rossi, Matteo LU
- organization
- publishing date
- 2021
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Free oscillations, Inverse theory, Structure of the Earth, Surface waves
- in
- Geophysical Journal International
- volume
- 225
- issue
- 3
- pages
- 17 pages
- publisher
- Oxford University Press
- external identifiers
-
- scopus:85112057946
- ISSN
- 0956-540X
- DOI
- 10.1093/gji/ggab068
- language
- English
- LU publication?
- yes
- id
- ea466f85-d790-41a8-a67c-f8c3fa6c3331
- date added to LUP
- 2021-09-02 17:13:21
- date last changed
- 2022-04-27 03:36:56
@article{ea466f85-d790-41a8-a67c-f8c3fa6c3331,
abstract = {{<p>The analysis of surface wave dispersion curves is a way to infer the vertical distribution of shear wave velocity. The range of applicability is extremely wide: going, for example, from seismological studies to geotechnical characterizations and exploration geophysics. However, the inversion of the dispersion curves is severely ill-posed and only limited efforts have been put in the development of effective regularization strategies. In particular, relatively simple smoothing regularization terms are commonly used, even when this is in contrast with the expected features of the investigated targets. To tackle this problem, stochastic approaches can be utilized, but they are too computationally expensive to be practical, at least, in case of large surveys. Instead, within a deterministic framework, we evaluate the applicability of a regularizer capable of providing reconstructions characterized by tunable levels of sparsity. This adjustable stabilizer is based on the minimum support regularization, applied before on other kinds of geophysical measurements, but never on surface wave data. We demonstrate the effectiveness of this stabilizer on (i) two benchmark—publicly available—data sets at crustal and near-surface scales and (ii) an experimental data set collected on a well-characterized site. In addition, we discuss a possible strategy for the estimation of the depth of investigation. This strategy relies on the integrated sensitivity kernel used for the inversion and calculated for each individual propagation mode. Moreover, we discuss the reliability, and possible caveats, of the direct interpretation of this particular estimation of the depth of investigation, especially in the presence of sharp boundary reconstructions.</p>}},
author = {{Vignoli, Giulio and Guillemoteau, Julien and Barreto, Jeniffer and Rossi, Matteo}},
issn = {{0956-540X}},
keywords = {{Free oscillations; Inverse theory; Structure of the Earth; Surface waves}},
language = {{eng}},
number = {{3}},
pages = {{1935--1951}},
publisher = {{Oxford University Press}},
series = {{Geophysical Journal International}},
title = {{Reconstruction, with tunable sparsity levels, of shear wave velocity profiles from surface wave data}},
url = {{http://dx.doi.org/10.1093/gji/ggab068}},
doi = {{10.1093/gji/ggab068}},
volume = {{225}},
year = {{2021}},
}