On the In-Seam Seismic Inverse Problem - Horizontal and Vertical Inversion of Love Seam Wave Data

Dobróka, Mihály; Fancsik, Tamás; Amran, A.

doi:10.3997/2214-4609.201409512

Cited by 1 publication

(1 citation statement)

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“…Series expansionbased inversion methods have been developed in details at the Department of Geophysics, University of Miskolc. Earlier a similar inversion algorithm was developed to solve the 2-D seismic guided-wave inverse problem by Dobróka et al (1995) and a 2-D seismic refraction inverse problem by Bernabini et al (1988) and by Ormos (2002) and Ormos and Daragó (2005), in which the lateral variation of the model was discretized by using series expansion and the inverse problem was formulated in terms of the expansion coefficients as unknowns. Further developments were presented by Cardarelli et al (2014) in combining geoelectric and seismic datasets in a joint tomographic procedure.…”

Section: Introductionmentioning

confidence: 99%

Results from the further development of CGI inversion on simulation and field data systems

Gyulai,

Turai,

Baracza

et al. 2024

CEuGeol

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A new series expansion-based method, the Combined Geoelectric Weighted Inversion (CGWI) procedure is presented and tested by using synthetic and in-field measured datasets. The method is an improved version of the Combined Geoelectric Inversion (CGI) robustified by involving Cauchy-Steiner weights in an Iteratively Reweighted Least Squares technique. The new procedure is compared to the Fourier series expansion-based 1.5D and the CGI methods as well as to the broadly applied RES2DINV inversion procedure. The field measurements are performed during stone exploration in an active quarry on the south-western slopes of the Mátra mountains, in northern Hungary. It is shown that the CGWI method gives stable and robust parameter estimation with acceptable accuracy. The comparison with other inversion methods is based on data distances, estimation errors and correlation parameters calculated on the base of the parameter correlation matrix.

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