• Corpus ID: 238744215

Seismic Tomography with Random Batch Gradient Reconstruction

@article{Hu2021SeismicTW,
  title={Seismic Tomography with Random Batch Gradient Reconstruction},
  author={Yixiao Hu and Lihui Chai and Zhongyi Huang and Xu Yang},
  journal={ArXiv},
  year={2021},
  volume={abs/2110.06455}
}
Seismic tomography solves high-dimensional optimization problems to image subsurface structures of Earth. In this paper, we propose to use random batch methods to construct the gradient used for iterations in seismic tomography. Specifically, we use the frozen Gaussian approximation to compute seismic wave propagation, and then construct stochastic gradients by random batch methods. The method inherits the spirit of stochastic gradient descent methods for solving highdimensional optimization… 

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References

SHOWING 1-10 OF 33 REFERENCES
Frozen Gaussian approximation for 3D seismic tomography
Three-dimensional (3D) wave-equation-based seismic tomography is computationally challenging in large scales and high-frequency regime. In this paper, we apply the frozen Gaussian approximation (FGA)
Frozen Gaussian approximation for 3-D elastic wave equation and seismic tomography
The purpose of this work is to generalize the frozen Gaussian approximation (FGA) theory to solve the 3-D elastic wave equation and use it as the forward modeling tool for seismic tomography with
Depth migration by the Gaussian beam summation method
Seismic depth migration aims to produce an image of seismic reflection interfaces. Ray methods are suitable for subsurface target-oriented imaging and are less costly compared to two-way
High-resolution seismic array imaging based on an SEM-FK hybrid method
We demonstrate the feasibility of high-resolution seismic array imaging based on teleseismic recordings using full numerical wave simulations. We develop a hybrid method that interfaces a
Seismic tomography of the southern California crust based on spectral‐element and adjoint methods
We iteratively improve a 3-D tomographic model of the southern California crust using numerical simulations of seismic wave propagation based on a spectral-element method (SEM) in combination with an
Seismic imaging: From classical to adjoint tomography
Abstract Seismic tomography has been a vital tool in probing the Earth's internal structure and enhancing our knowledge of dynamical processes in the Earth's crust and mantle. While various
Seismic modeling using the frozen Gaussian approximation
We adopt the frozen Gaussian approximation (FGA) for modeling seismic waves. The method belongs to the category of ray-based beam methods. It decomposes seismic wavefield into a set of Gaussian
Tomography, Adjoint Methods, Time-Reversal, and Banana-Doughnut Kernels
SUMMARY We draw connections between seismic tomography, adjoint methods popular in climate and ocean dynamics, time-reversal imaging and finite-frequency ‘banana-doughnut’ kernels. We demonstrate
Gaussian beam migration
Just as synthetic seismic data can be created by expressing the wave field radiating from a seismic source as a set of Gaussian beams, recorded data can be downward continued by expressing the
Adjoint Tomography of the Southern California Crust
TLDR
A three-dimensional seismological model of the southern California crust is developed that illuminates shallow features such as sedimentary basins and compositional contrasts across faults, and reveals crustal features at depth that aid in the tectonic reconstruction of southern California.
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