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Comparison between the nearly perfectly matched layer and unsplit convolutional perfectly matched layer methods using acoustic wave modeling

JINGYI CHEN1,2 ,  CHAOYING ZHANG3 ,  RALPH PHILLIP BORDING4
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1 Department of Geosciences, College of Engineering and Natural Sciences, University of Tulsa. Tulsa, OK 74104, U.S.A. jingyi-chen@utulsa.edu,
3 Department of Geological Sciences, University of Saskatchewan, Saskatoon, SK, Canada S7N 5E2. chaoying.zhang@usask.ca,
4 Computer Science Chair, Alabama A&M University, Normal, Alabama 35762, U.S.A. phil.bording@aamu.edu,
JSE 2010, 19(2), 173–185;
Submitted: 9 June 2025 | Revised: 9 June 2025 | Accepted: 9 June 2025 | Published: 9 June 2025
© 2025 by the Authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
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Abstract

Chen, J., Zhang, C. and Bording, R.P., 2010. Comparison between the nearly perfectly matched layer and unsplit convolutional perfectly matched layer methods using acoustic wave modeling. Journal of Seismic Exploration, 19: 173-185. The unsplit convolutional perfectly matched layer (CPML) and nearly perfectly matched layer (NPML) methods both have been proven to be very efficient algorithms for eliminating artificial reflections from the edges of the synthetic seismic wave models. Their absorbing performance and efficiency have been studied in separate works in several papers. Obviously, if we provide numerical comparisons between CPML and NPML in seismic modeling, it is very helpful to understand their performances and differences. In this paper, we will carry out these comparisons using 2D acoustic wave modeling codes with staggered-grid finite-difference schemes. For the implementation of the finite-difference operator, we employ fourth-order accuracy methods in space and second-order accuracy methods in time. In the model tests, we demonstrate that NPML has the same absorbing performance as CPML, with some very minor differences. We suggest that more analysis will be needed to study how these methods perform in the wide varieties of complex media that are typically used in seismic modeling.

Keywords
nearly perfectly matched layer
unsplit convolutional perfectly matched layer
acoustic modeling
staggered-grid finite-difference
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Journal of Seismic Exploration, Electronic ISSN: 0963-0651 Print ISSN: 0963-0651, Published by AccScience Publishing
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