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 …

To simulate seismic wavefields with a frequency-domain wave equation, conventional
numerical methods must solve the equation sequentially to obtain the wavefields for different …

We review five types of physics-informed machine-learning (PIML) algorithms for inversion
and modeling of geophysical data. Such algorithms use the combination of a data-driven …

Building subsurface models is a very important but challenging task in hydrocarbon
exploration and development. The subsurface elastic properties are usually sourced from …

Full-waveform inversion (FWI) is a popularly used high-resolution seismic inversion method.
It relies on the measure of the misfit between observed data and predicted data. Due to the …

Full waveform inversion (FWI) has the potential to provide high-resolution subsurface model
estimations. However, due to limitations in observation, eg, regional noise, limited aperture …

With the emergence of massive seismic data sets, surface wave methods using deep
learning (DL) can effectively obtain shear wave velocity (Vs) structure for non-invasive near …

In seismic wave simulation, solving the wave equation in the frequency domain requires
calculating the inverse of the impedance matrix. The total cost strictly depends on the …

Elastic full-waveform inversion (FWI) can construct high-resolution P-wave velocity, S-wave
velocity, and density models in complex geological settings. However, several factors make …

Seismic inversion is an indispensable part of the earth exploration to precisely obtain the
properties of subsurface media based on seismic data. However, the lack or inaccuracy of …