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Surface‐wave inversion using a direct search algorithm and its application to ambient vibration measurements
Author(s) -
Wathelet M.,
Jongmans D.,
Ohrnberger M.
Publication year - 2004
Publication title -
near surface geophysics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.639
H-Index - 39
eISSN - 1873-0604
pISSN - 1569-4445
DOI - 10.3997/1873-0604.2004018
Subject(s) - a priori and a posteriori , algorithm , inversion (geology) , rayleigh wave , geology , synthetic data , maxima and minima , computation , regional geology , surface wave , hydrogeology , computer science , optics , seismology , mathematics , mathematical analysis , physics , geotechnical engineering , tectonics , philosophy , epistemology , metamorphic petrology
Passive recordings of seismic noise are increasingly used in earthquake engineering to measure in situ the shear‐wave velocity profile at a given site. Ambient vibrations, which are assumed to be mainly composed of surface waves, can be used to determine the Rayleigh‐wave dispersion curve, with the advantage of not requiring artificial sources. Due to the data uncertainties and the non‐linearity of the problem itself, the solution of the dispersion‐curve inversion is generally non‐unique. Stochastic search methods such as the neighbourhood algorithm allow searches for minima of the misfit function by investigating the whole parameter space. Due to the limited number of parameters in surface‐wave inversion, they constitute an attractive alternative to linearized methods. An efficient tool using the neighbourhood algorithm was developed to invert the one‐dimensionalV sprofile from passive or active source experiments. As the number of generated models is usually high in stochastic techniques, special attention was paid to the optimization of the forward computations. Also, the possibility of inserting a priori information into the parametrization was introduced in the code. This new numerical tool was successfully tested on synthetic data, with and without a priori information. We also present an application to real‐array data measured at a site in Brussels (Belgium), the geology of which consists of about 115 m of sand and clay layers overlying a Palaeozoic basement. On this site, active and passive source data proved to be complementary and the method allowed the retrieval of aV sprofile consistent with borehole data available at the same location.