A Gauss-Newton full-waveform inversion in PML-truncated domains using scalar probing waves
- Authors
- Pakravan, Alireza; Kang, Jun Won; Newtson, Craig M.
- Issue Date
- 1-Dec-2017
- Publisher
- ACADEMIC PRESS INC ELSEVIER SCIENCE
- Keywords
- Gauss-Newton full-waveform inversion; Perfectly matched layer; Hybrid unsplit-field PML; Shear wave velocity; Karush-Kuhn-Tucker conditions
- Citation
- JOURNAL OF COMPUTATIONAL PHYSICS, v.350, pp.824 - 846
- Journal Title
- JOURNAL OF COMPUTATIONAL PHYSICS
- Volume
- 350
- Start Page
- 824
- End Page
- 846
- URI
- https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/4921
- DOI
- 10.1016/j.jcp.2017.09.017
- ISSN
- 0021-9991
- Abstract
- This study considers the characterization of subsurface shear wave velocity profiles in semi-infinite media using scalar waves. Using surficial responses caused by probing waves, a reconstruction of the material profile is sought using a Gauss-Newton full-waveform inversion method in a two-dimensional domain truncated by perfectly matched layer (PML) wave-absorbing boundaries. The PML is introduced to limit the semi-infinite extent of the half-space and to prevent reflections from the truncated boundaries. A hybrid unsplit-field PML is formulated in the inversion framework to enable more efficient wave simulations than with a fully mixed PML. The full-waveform inversion method is based on a constrained optimization framework that is implemented using Karush-Kuhn-Tucker (KKT) optimality conditions to minimize the objective functional augmented by PML-endowed wave equations via Lagrange multipliers. The KKT conditions consist of state, adjoint, and control problems, and are solved iteratively to update the shear wave velocity profile of the PML-truncated domain. Numerical examples show that the developed Gauss-Newton inversion method is accurate enough and more efficient than another inversion method. The algorithm's performance is demonstrated by the numerical examples including the case of noisy measurement responses and the case of reduced number of sources and receivers. (C) 2017 Elsevier Inc. All rights reserved.
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