Abstract

Horizontal-to-Vertical Spectral Ratios (HVSR) and Rayleigh group velocity dispersion curves (DC) can be used to estimate the shallow S-wave velocity () structure. Knowing the structure is important for geophysical data interpretation either in order to better constrain data inversions for P-wave velocity () structures such as travel time tomography or full waveform inversions or to directly study the structure for geo-engineering purposes (e.g., ground motion prediction). The joint inversion of HVSR and dispersion data for 1D structure allows characterising the uppermost crust and near surface, where the HVSR data ( to ) are most sensitive while the dispersion data (1 to ) constrain the deeper model which would, otherwise, add complexity to the HVSR data inversion and adversely affect its convergence. During a large-scale experiment, 197 three-component short-period stations, 41 broad band instruments and 190 geophones were continuously operated for 6 months (April to October 2017) covering an area of approximately with a site spacing of approximately 1 to . Joint inversion of HVSR and DC allowed estimating and, to some extent density, down to depths of around . Broadband and short period instruments performed statistically better than geophone nodes due to the latter’s gap in sensitivity between HVSR and DC. It may be possible to use HVSR data in a joint inversion with DC, increasing resolution for the shallower layers and/or alleviating the absence of short period DC data, which may be harder to obtain. By including HVSR to DC inversions, confidence improvements of two to three times for layers above were achieved. Furthermore, HVSR/DC joint inversion may be useful to generate initial models for 3D tomographic inversions in large scale deployments. Lastly, the joint inversion of HVSR and DC data can be sensitive to density but this sensitivity is situational and depends strongly on the other inversion parameters, namely and . Density estimates from a HVSR/DC joint inversion should be treated with care, while some subsurface structures may be sensitive, others are clearly not. Inclusion of gravity inversion to HVSR/DC joint inversion may be possible and prove useful.

Highlights

  • The horizontal-to-vertical spectral ratio (HVSR) or Nakamura’s technique [1,2,3] is widely used in seismic exploration for constraining shallow geologic structures [4]

  • While it is known that HVSR and dispersion curves (DC) data complement each other, here we want to study what specific improvement can be expected from a joint inversion

  • At depths larger than 300 m, the layer VS variance estimates are equal between both inversion strategies. These results indicate that the sensitivity of the present HVSR data reaches at least 300 m before it declines, while the present DC data are most sensitive for depths larger than 300 m

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Summary

Introduction

The horizontal-to-vertical spectral ratio (HVSR) or Nakamura’s technique [1,2,3] is widely used in seismic exploration for constraining shallow geologic structures [4]. While the experiment attempts to shed light on the regional crustal structure of the Mauléon Basin in the Western Pyrenees with a large-N array, it is designed such that it allows inferring about the individual and joint performance of different passive seismic methods, such as local earthquake tomography (LET), ambient noise tomography (ANT) and, intrinsically, HVSR. The inversion of dispersion curves experiences problems when a suboptimal initial range of near surface velocities causes low crustal velocities, and LET tends to overestimate near surface velocities, which may reduce overall resolution and accuracy For both methods, HVSR can supply constrains on the near surface model parameters that allow distinguishing otherwise valid models and, complementing LET and ANT. HVSR to 1D inversions of Rayleigh wave velocity dispersion for the shallow shear wave velocity (VS ) structure

Maupasacq Experiment
Study Area
Acquisition
Purpose of Horizontal-to-Vertical Spectral Ratio
Data Processing and Inversion Methodologies
Data Preparation and Processing
Inversion of DCs and Joint Inversion with HVSR
Horizontal-to-Vertical and Dispersion Curves
Benefit of 1D Joint Inversion of HVSR and DC
VS 3D Model and Comparison with Local-Earthquake Tomography
Density Model
Conclusions
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