Ambient noise and earthquake HVSR modelling for site characterization in southern mainland, Gujarat

Site characterization and delineation of possible shallow shear-velocity structures are conducted from the study of the horizontal to vertical spectral ratio (HVSR) measurements using the ambient noise or microtremor (herein called classical HVSR), extracted Rayleigh wave from the ambient noise data (herein called standard HVSR) and earthquake (herein called earthquake HVSR) data in the Surat district of mainland Gujarat, India. These locations are the hub of many mining and industrial projects like oil and natural gas, which need to function safely within the seismic hazard and ground shaking limits. From the classical and standard HVSR datasets, estimates of the predominant resonant frequency of the soil are obtained, from which first order inversions are carried out around the predominant frequency to provide a fair estimate of thickness of the regimented layer over a hard seismic substratum up to a depth of 100 m. In the standard HVSR datasets, the Rayleigh wave ellipticity curves are extracted with time–frequency analysis using continuous wavelet transforms. This is followed by the Rayleigh wave ellipticity inversion approach to derive a first order approximate sedimentary shear velocity structure. We also compute HVSR measurements using earthquakes. The noise and earthquake HVSR curves are well-matched in terms of the predominant frequencies and range from 3.8 to 16.7 Hz and 3.2 to 16.5, respectively. The estimated VS30 values (the average shear wave velocity (VS) for the top 30 m of the soil) vary from 520 to 1350 m/s, matching well with some of the geotechnical studies conducted here. The study emphasizes the effectiveness of the single station HVSR method in determination of hitherto unknown soil structures as economical and non-invasive exploration viability and proving quite useful for critical centres of industrial establishments.

Durgada N., K. Sivaram, N. P. Rao and H V S Satyanarayana, J. Earth Syst. Sci. (2020)129:195 https://doi.org/10.1007/s12040-020-01443-8