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Review Paper | Open Access

Overview of computation strategies on the dispersion analysis for explicit finite difference solution of acoustic wave equation

Jian-Ping Huanga,b, Wei-Ting Penga,b( ), Ji-Dong Yanga,b, Lu-Feng Loua,b
School of Geosciences, China University of Petroleum (East China), Qingdao, 266580, Shandong, China
Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao, 266000, Shandong, China

Edited by Jie Hao and Meng-Jiao Zhou

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Abstract

Finite-difference (FD) method is the most extensively employed numerical modeling technique. Nevertheless, when using the FD method to simulate the seismic wave propagation, the large spatial or temporal sampling interval can lead to dispersion errors and numerical instability. In the FD scheme, the key factor in determining both dispersion errors and stability is the selection of the FD weights. Thus, How to obtain appropriate FD weights to guarantee a stable numerical modeling process with minimum dispersion error is critical. The FD weights computation strategies can be classified into three types based on different computational ideologies, window function strategy, optimization strategy, and Taylor expansion strategy. In this paper, we provide a comprehensive overview of these three strategies by presenting their fundamental theories. We conduct a set of comparative analyses of their strengths and weaknesses through various analysis tests and numerical modelings. According to these comparisons, we provide two potential research directions of this field: Firstly, the development of a computational strategy for FD weights that enhances stability; Secondly, obtaining FD weights that exhibit a wide bandwidth while minimizing dispersion errors.

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Petroleum Science
Pages 2311-2328

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Cite this article:
Huang J-P, Peng W-T, Yang J-D, et al. Overview of computation strategies on the dispersion analysis for explicit finite difference solution of acoustic wave equation. Petroleum Science, 2024, 21(4): 2311-2328. https://doi.org/10.1016/j.petsci.2024.02.003

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Received: 04 April 2023
Revised: 20 December 2023
Accepted: 03 February 2024
Published: 05 February 2024
© 2024 The Authors.

This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).