High-resolution surface wave dispersion spectrum computation based on iterative threshold shrinkage algorithm and its application to irregularly sampled data
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...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-07-01
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| Series: | Frontiers in Earth Science |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/feart.2025.1600734/full |
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| Summary: | 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 shear-wave 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. |
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| ISSN: | 2296-6463 |