Seismic waves from earthquakes and other sources are used to infer the structure and
properties of Earth's interior. The availability of large-scale seismic datasets and the …

The goal of seismic inversion is to obtain subsurface properties from surface measurements.
Seismic images have proven valuable, even crucial, for a variety of applications, including …

One of the key objectives in geophysics is to characterize the subsurface through the
process of analyzing and interpreting geophysical field data that are typically acquired at the …

Exploration seismology uses reflected and refracted seismic waves, emitted from a
controlled (active) source into the ground, and recorded by an array of seismic sensors …

Full waveform inversion (FWI) is widely used in geophysics to reconstruct high-resolution
velocity maps from seismic data. The recent success of data-driven FWI methods results in a …

Deep learning (DL) has achieved promising results for impedance inversion via seismic
data. Generally, these networks, composed of convolution layers and residual blocks, tend …

Full-waveform inversion (FWI) is an accurate imaging approach for modeling the velocity
structure by minimizing the misfit between recorded and predicted seismic waveforms …

The rapid growth of deep learning research, including within the field of computational
mechanics, has resulted in an extensive and diverse body of literature. To help researchers …

The influence of earthquake disasters on human social life is positively related to the
magnitude and intensity of the earthquake, and effectively avoiding casualties and property …

This paper investigates unsupervised learning of Full-Waveform Inversion (FWI), which has
been widely used in geophysics to estimate subsurface velocity maps from seismic data …