A Nonbalanced Staggered-Grid FDTD Scheme for the First-Order Elastic-Wave Extrapolation and Reverse-Time Migration

In this study, an efficient and accurate staggered-grid finite-difference time-domain method to solve the two-dimensional (2-D) first-order stress-velocity elastic-wave equation is proposed. In the conventional implementation of the staggered-grid finite-difference (SGFD) method, the same SGFD opera...

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Bibliographic Details
Published in:IEEE journal of selected topics in applied earth observations and remote sensing 2022, Vol.15, p.4772-4781
Main Authors: Liang, Wenquan, Chen, Guoxin, Wang, Yanfei, Cao, Jingjie, Chen, Jinxin
Format: Article
Language:English
Subjects:
Accuracy
Computer applications
Dispersion
Elastic waves
Finite difference methods
Finite difference time domain method
Finite element analysis
geophysics computing
Imaging
Mathematical analysis
Mathematical models
Methods
Numerical methods
Operators
Propagation
reverse-time migration (RTM)
Time-domain analysis
Wave equations
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Summary:In this study, an efficient and accurate staggered-grid finite-difference time-domain method to solve the two-dimensional (2-D) first-order stress-velocity elastic-wave equation is proposed. In the conventional implementation of the staggered-grid finite-difference (SGFD) method, the same SGFD operator is used to approximate the spatial derivatives. However, we propose a numerical method based on the mixed SGFD operators that are more efficient but similar in accuracy when compared with a uniform SGFD operator. We refer to the proposed method as the nonbalanced SGFD numerical scheme that combines the high-order SGFD operators with the second-order SGFD operators. The suitability of the proposed scheme is verified by dispersion analysis. Through SGFD modeling and reverse-time migration examples, we demonstrate that the proposed nonbalanced scheme offers a similar level of accuracy with a lower computational cost compared with the time-consuming conventional SGFD method.
ISSN:1939-1404
2151-1535
DOI:10.1109/JSTARS.2022.3181000