Estimating S-wave velocity profiles from horizontal-to-vertical spectral ratios based on deep learning
Year: 2024
Type: article
Abstract: S-wave velocity (Vs) profile or time averaged Vs to 30 m depth (V S30 ) is indispensable information to estimate the local site amplification of ground motion from earthquakes. We use a horizontal-to-vertical spectral ratio (H/V) of seismic ambient noise to estimate the Vs profiles or V S30 . The measurement of H/V is easier, compared to active surface wave methods (MASW) or microtremor array measurements (MAM). The inversion of H/V is non-unique and it is impossible to obtain unique Vs profiles. We apply deep learning to estimate the Vs profile from H/V together with other information including site coordinates, deep bedrock depths, and geomorphological classification. The pairs of H/V spectra (input layer) and Vs profiles (output layer) are used as training data. An input layer consists of an observed H/V spectrum, site coordinates, deep bedrock depths, and geomorphological classification, and an output layer is a velocity profile. We applied the method to the South Kanto Plain, Japan. We measured MASW, MAM and H/V at approximately 2300 sites. The pairs of H/V spectrum together with their coordinates, geomorphological classification etc. and Vs profile obtained from the inversion of dispersion curve and H/V, compose the training data. A trained neural network predicts Vs profiles from the observed H/V spectra with other information. Predicted Vs profiles and their V S30 are reasonably consistent with true Vs profiles and their V S30 . The results implied that the deep learning could estimate Vs profile from H/V together with other information.
Source: SOILS AND FOUNDATIONS
Authors: Koichi Hayashi, Toru Suzuki, Tomio Inazaki, Chisato Konishi, Haruhiko Suzuki, Hisanori Matsuyama
Institutions: Kyoto University, OYO Corporation (Japan)
Language: English
Topic: Seismic Waves and Analysis
Subfield: Geophysics
Field: Earth and Planetary Sciences
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,200
OpenAlex ID: W4403930923