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Simultaneous Algebraic Reconstruction Technique (SART) for Retrieving 1D Shear-Wave Quality Factor Qs Profiles Using Seismic Noise

Session: Advances in Upper Crustal Geophysical Characterization I

Type: Oral

Date: 4/21/2021

Presentation Time: 10:00 AM Pacific

Description: 

Nowadays seismic noise has become a useful tool in site effects estimation. Although generally it is used to retrieve the shear-wave velocity (V_s) and the fundamental resonance frequency of sedimentary covers, it also has potential to estimate the seismic waves attenuation characteristics and, in particular, the related shear-wave quality factor (Q_S).

Parolai (2014) proposed a method based on a least squares algorithm with positivity Q_S constraint (Menke, 1989) for obtaining 1D Q_S versus depth profiles from microarrays. The results were compared with Q_S results derived from independent geophysical surveys and showed a good agreement. However, the proposed approach requires accurate trial-and-error tests of the damping factors in the preliminary phase, in order to obtain robust Q_S outcomes.

This work investigates whether the Simultaneous Algebraic Reconstruction Technique (SART) (Andersen and Kak, 1984) can be used in the approach of Parolai (2014) as an alternative to the least squares algorithm for avoiding the trial-and-error procedure. SART is an iterative reconstruction algorithm, that offers the advantage of setting a positivity Q_S constraint to the solutions with ease. First, the new technique is tested and calibrated in two test sites where 1D Q_S profiles were retrieved in previous works with the approach of Parolai (2014). The results show that the new method can be useful to obtain robust Q_S values by setting the relaxation parameter and the number of iterations in the SART procedure in pre-defined narrow value ranges. Then, the technique is applied in another test site placed at Piana di Toppo, Travesio (North-East Italy), where Q estimates are available from independent geophysical methods. The results obtained by setting the inversion parameters in the ranges previously estimated indicate that SART can be promising for calculating 1D Q_S profiles at a local scale.

Presenting Author: Ilaria Dreossi

Student Presenter: Yes

Authors