Implicit neural representations with periodic activation functions

V Sitzmann, J Martel, A Bergman… - Advances in neural …, 2020 - proceedings.neurips.cc
Implicitly defined, continuous, differentiable signal representations parameterized by neural
networks have emerged as a powerful paradigm, offering many possible benefits over …

Seismic wavefield imaging of Earth's interior across scales

J Tromp - Nature Reviews Earth & Environment, 2020 - nature.com
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 …

A review on reflection-waveform inversion

G Yao, D Wu, SX Wang - Petroleum Science, 2020 - Springer
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 …

Solving the frequency-domain acoustic VTI wave equation using physics-informed neural networks

C Song, T Alkhalifah, UB Waheed - Geophysical Journal …, 2021 - academic.oup.com
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 …

Adaptive waveform inversion: Theory

M Warner, L Guasch - Geophysics, 2016 - library.seg.org
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 via physics-informed neural networks

C Song, TA Alkhalifah - IEEE Transactions on Geoscience and …, 2021 - ieeexplore.ieee.org
Wavefield reconstruction inversion (WRI) formulates a PDE-constrained optimization
problem to reduce cycle skip** in full-waveform inversion (FWI). WRI is often implemented …

An introduction to full waveform inversion

J Virieux, A Asnaashari, R Brossier… - Encyclopedia of …, 2017 - library.seg.org
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 …

[HTML][HTML] Wavefield solutions from machine learned functions constrained by the Helmholtz equation

T Alkhalifah, C Song, U bin Waheed, Q Hao - Artificial Intelligence in …, 2021 - Elsevier
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 …

Improving full-waveform inversion by wavefield reconstruction with the alternating direction method of multipliers

HS Aghamiry, A Gholami, S Operto - Geophysics, 2019 - pubs.geoscienceworld.org
Full-waveform inversion (FWI) is an iterative nonlinear waveform matching procedure
subject to wave-equation constraint. FWI is highly nonlinear when the wave-equation …

Multi-task learning for low-frequency extrapolation and elastic model building from seismic data

O Ovcharenko, V Kazei, TA Alkhalifah… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Low-frequency (LF) signal content in seismic data as well as a realistic initial model are key
ingredients for robust and efficient full-waveform inversions (FWIs). However, acquiring LF …