Seismic full-waveform inversion (FWI) for imaging Earth's interior was introduced in the late
1970s. Its ultimate goal is to use all of the information in a seismogram to understand the …

Full-waveform inversion (FWI) utilizes optimization methods to recover an optimal Earth
model to best fit the observed seismic record in a sense of a predefined norm. Since FWI …

Implicitly defined, continuous, differentiable signal representations parameterized by neural
networks have emerged as a powerful paradigm, offering many possible benefits over …

Frequency-domain wavefield solutions corresponding to the anisotropic acoustic wave
equation can be used to describe the anisotropic nature of the Earth. To solve a frequency …

Conventional full-waveform seismic inversion attempts to find a model of the subsurface that
is able to predict observed seismic waveforms exactly; it proceeds by minimizing the …

Wavefield reconstruction inversion (WRI) formulates a PDE-constrained optimization
problem to reduce cycle skipping in full-waveform inversion (FWI). WRI is often implemented …

Full waveform inversion (FWI) is a high-resolution seismic imaging technique that is based
on using the entire content of seismic traces for extracting physical parameters of the …

Solving the wave equation is one of the most (if not the most) fundamental problems we face
as we try to illuminate the Earth using recorded seismic data. The Helmholtz equation …

Full waveform inversion (FWI) aims to reconstruct high-resolution subsurface models from
the full wavefield, which includes diving waves, post-critical reflections and short-spread …

Many inverse and parameter estimation problems can be written as PDE-constrained
optimization problems. The goal is to infer the parameters, typically coefficients of the PDE …