Zobrazeno 1 - 10
of 156
pro vyhledávání: '"Operto, Stéphane"'
Full-waveform inversion (FWI) with extended sources first computes wavefields with data-driven source extensions, such that the simulated data in inaccurate velocity models match the observed counterpart well enough to prevent cycle skipping. Then, t
Externí odkaz:
http://arxiv.org/abs/2303.01009
Autor:
Operto, Stephane, Gholami, Ali, Aghamiry, Hossein S., Guo, Gaoshan, Mamfoumbi, Frichnel, Beller, Stephen
Full Waveform Inversion can be made immune to cycle skipping by matching the recorded data arbitrarily well from inaccurate subsurface models. To achieve this goal, the simulated wavefields can be computed in an extended search space as the solution
Externí odkaz:
http://arxiv.org/abs/2212.10141
Frequency-domain simulation of seismic waves plays an important role in seismic inversion, but it remains challenging in large models. The recently proposed physics-informed neural network (PINN), as an effective deep learning method, has achieved su
Externí odkaz:
http://arxiv.org/abs/2208.08276
Implementation of the standard full waveform inversion (FWI) poses difficulties as the initial model offsets from the true model. The wavefield reconstruction inversion (WRI) was proposed to mitigate these difficulties by relaxing the wave-equation c
Externí odkaz:
http://arxiv.org/abs/2206.07367
Full-waveform inversion (FWI) is a high-resolution and computationally intensive imaging technique to reconstruct unknown parameters in the computational model in which the waves propagate; however, an accurate model of only part of this medium is re
Externí odkaz:
http://arxiv.org/abs/2203.13133
Full-waveform inversion (FWI) is a seismic imaging method that provides quantitative inference about subsurface properties with a wavelength-scale resolution. Its frequency-domain formulation is computationally efficient when processing only a few di
Externí odkaz:
http://arxiv.org/abs/2202.08558
The full-waveform inversion (FWI) addresses the computation and characterization of subsurface model parameters by matching predicted data to observed seismograms in the frame of nonlinear optimization. We formulate FWI as a nonlinearly constrained o
Externí odkaz:
http://arxiv.org/abs/2108.11267
Efficient frequency-domain Full Waveform Inversion (FWI) of long-offset/wide-azimuth node data can be designed with a few discrete frequencies. However, 3D frequency-domain seismic modeling remains challenging since it requires solving a large and sp
Externí odkaz:
http://arxiv.org/abs/2108.08730
Partial differential equation (PDE) constrained optimization problems such as seismic full waveform inversion (FWI) frequently arise in the geoscience and related fields. For such problems, many observations are usually gathered by multiple sources,
Externí odkaz:
http://arxiv.org/abs/2108.03961
The augmented Lagrangian (AL) method provides a flexible and efficient framework for solving extended-space full-waveform inversion (FWI), a constrained nonlinear optimization problem whereby we seek model parameters and wavefields that minimize the
Externí odkaz:
http://arxiv.org/abs/2106.14065