Results 11 to 20 of about 3,297,474 (208)
ω-FWI: Robust full-waveform inversion with Fourier-based metric [PDF]
, 2022 Full-waveform inversion is a cutting-edge methodology for recovering high-resolution subsurface models. However, one of the main conventional full-waveform optimization problems challenges is cycle-skipping, usually leading us to an inaccurate local ...
Izzatullah, Muhammad +1 more
core +2 more sources
$\omega$-FWI: Robust full-waveform inversion with Fourier-based metric [PDF]
, 2022 Full-waveform inversion is a cutting-edge methodology for recovering high-resolution subsurface models. However, one of the main conventional full-waveform optimization problems challenges is cycle-skipping, usually leading us to an inaccurate local ...
Izzatullah, Muhammad, Alkhalifah, Tariq
core +3 more sources
$\mathbf{\mathbb{E}^{FWI}}$: Multi-parameter Benchmark Datasets for Elastic Full Waveform Inversion of Geophysical Properties [PDF]
Advances in Neural Information Processing Systems 36, 2023 Elastic geophysical properties (such as P- and S-wave velocities) are of great importance to various subsurface applications like CO$_2$ sequestration and energy exploration (e.g., hydrogen and geothermal). Elastic full waveform inversion (FWI) is widely
Feng, Shihang +8 more
core +4 more sources
Gauss-Newton and L-BFGS Methods in Full Waveform Inversion (FWI) [PDF]
, 2022 Full waveform inversion (FWI) is a recent powerful method in the area of seismic imaging where it used for reconstructing high-resolution images of the subsurface structure from local measurements of the seismic wavefield.
Muhammad Izzatullah +7 more
core +2 more sources
Journal of Geophysical Research: Machine Learning and ComputationFull waveform inversion (FWI) reconstructs subsurface models by minimizing the mismatch between observed and simulated seismic data. However, the strong nonlinearity of the inversion problem makes gradient‐based optimization highly sensitive to ...
Ning Wang +3 more
doaj +2 more sources
Transfer Learning Enhanced Full Waveform Inversion [PDF]
, 2023 We propose a way to favorably employ neural networks in the field of non-destructive testing using Full Waveform Inversion (FWI). The presented methodology discretizes the unknown material distribution in the domain with a neural network within an ...
Singh, Divya +2 more
core +1 more source
3D Bayesian Variational Full Waveform Inversion [PDF]
, 2022 Seismic full-waveform inversion (FWI) provides high resolution images of the subsurface by exploiting information in the recorded seismic waveforms. This is achieved by solving a highly nonnlinear and nonunique inverse problem.
Zhang, Xin +5 more
core +1 more source
Cross-correlation Full Waveform Inversion for Sound Speed Reconstruction in Ultrasound Computed Tomography [PDF]
, 2022 Ultrasound computed tomography (USCT) is considered to have great potential for breast cancer screening. Compared with the ray based methods, the reconstructed image using full waveform inversion (FWI) methods have higher spatial resolution. However, the
Zhao, Yue +4 more
core +6 more sources
Waveform inversion of the S reflector west of Spain: fine structure of a detachment fault. [PDF]
, 2005 The S reflection west of Iberia has been interpreted as a low-angle detachment fault separating crustal fault blocks from partially serpentinized mantle. We apply full waveform inversion to investigate the fine structure of S.
Minshull, TA +7 more
core +1 more source
Analysis of the covariance matrix in FWI through density of covariance maps
CT&F Ciencia, Tecnología & Futuro, 2020 Full waveform inversion (FWI) is a tool for the inversion of seismic data. There are several sources of uncertainty in the results provided by FWI. The quantification of such uncertainties has been studied through the resolution matrix (Res), which rests
Anyeres Neider Jimenez +3 more
doaj +1 more source