METHODS article
Front. Earth Sci.
Sec. Solid Earth Geophysics
Volume 13 - 2025 | doi: 10.3389/feart.2025.1600734
This article is part of the Research TopicExploring Near-Surface Geophysics and Tectonics: From Conventional Modeling to AI SolutionsView all articles
High-Resolution Surface Wave Dispersion Spectrum Computation Based on Iterative Threshold Shrinkage Algorithm and its Application to Irregularly Sampled Data
Provisionally accepted
- 1Southwest Petroleum University, Chengdu, China
- 2SLB, Houston, Texas, USA, Texas, United States
- 3Geophysical Investigation Institute of Sichuan Province, chengdu, China
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Surface waves have proven to be valuable instruments in subsurface investigation, finding applications in diverse fields such as hydrocarbon and mineral resource exploration. The computation of dispersion spectrums is a critical step in multi-channel analysis of both active and passive surface waves for imaging subsurface shear-wave velocity distribution. A high-resolution surface-wave dispersion spectrum is fundamental for accurate dispersion curve picking and shearwave velocity structure inversion. This paper presents a high-resolution method for surface-wave dispersion spectrum computation using Tau-P transform implemented with an iterative threshold shrinkage algorithm scheme. In this method, Tau-P transform is formulated as a sparse inversion scheme, and the Tau-P coefficients are iteratively thresholded to achieve a high-resolution Tau-P domain representation. By transforming surface wave traces into the Tau-P domain with the above sparse inversion algorithm and then converting them to the frequency phase velocity domain, a high-resolution dispersion spectrum is achieved. This method can also be applied to compute surface wave dispersion spectrum for irregularly sampled data. Synthetic tests of the proposed method demonstrate that the proposed scheme generates a high-resolution surface-wave dispersion spectrum that matches the theoretical dispersion curve. Field data tests also demonstrate that the dispersion spectrum generated with the proposed algorithm shows higher resolution and less noise. Also, the resultant shear-velocity inversion result matches better with the collocated micrologging result than the result associated with the conventional Tau-P trans-form algorithm, indicating a higher-precision inversion result.
Keywords: surface waves, dispersion curves, Tau-p transform, high resolution, Shear-wave velocity, irregularly sampled data
Received: 26 Mar 2025; Accepted: 30 Jun 2025.
Copyright: © 2025 Luo, Huang, Cao, Yao, Xu, Zhao and Bin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Weiping Cao, SLB, Houston, Texas, USA, Texas, United States
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