Academic Journal
Construction of shallow shear wave velocity structure model via trans-dimensional Bayesian inversion of Rayleigh wave dispersion curves
| Τίτλος: | Construction of shallow shear wave velocity structure model via trans-dimensional Bayesian inversion of Rayleigh wave dispersion curves |
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| Συγγραφείς: | Che, Han, Shen, Hongyan, Wang, Hao, Feng, Shisheng, Wang, Kanglong, Xu, Haihong, Li, Min, Wang, Kai, Hao, Chen, Xie, Zhihui |
| Συνεισφορές: | National Natural Science Foundation of China, Natural Science Basic Research Project of Shaanxi Province |
| Πηγή: | Geophysical Journal International ; volume 246, issue 2 ; ISSN 0956-540X 1365-246X |
| Στοιχεία εκδότη: | Oxford University Press (OUP) |
| Έτος έκδοσης: | 2026 |
| Περιγραφή: | SUMMARY Rayleigh wave dispersion curves inversion is an important method for shallow shear wave velocity structure imaging, which can be achieved through different frameworks such as deterministic inversion and Bayesian inversion. The deterministic methods with fixed parametrization usually require pre-set model complexity, and are difficult to directly provide posterior uncertainty estimation. In contrast, trans-dimensional Bayesian method can probabilistically estimate the dimensions of the model during the sampling process and quantify the uncertainty of the inversion results. However, in the inversion of multimode Rayleigh wave dispersion curves, the posterior space usually has high-dimensional, multimodal and strongly nonlinear characteristics. How to achieve efficient posterior exploration and stable trans-dimensional mixing is still a key issue in practical applications. In response to this issue, we constructed and evaluated a trans-dimensional parallel tempering reversible jump Markov Chain Monte Carlo (PT-rjMCMC) inversion workflow for multimodal Rayleigh wave dispersion curves in shear wave velocity imaging, denoted as All-Pair-Sweep PT-rjMCMC (APS-PT-rjMCMC). The method integrated Voronoi trans-dimensional parametrization, multimodal dispersion likelihood function, reversible jump model update and parallel tempering sampling into a unified framework. In the replica exchange stage, it adopted an all-pair-sweep replica-exchange schedule with randomized ordering to enhance the inter chain information propagation and trans-dimensional mixing ability under a limited number of temperature chains. The inversion results of synthesized model and measured data indicated that compared with the benchmark implementation, the workflow exhibited better performance in convergence behaviour, posterior structure recovery and layer identification. Our technology provides a solution that combines adaptability and reliability for fine survey of shallow geological structures. It is effectively improving the inversion ... |
| Τύπος εγγράφου: | article in journal/newspaper |
| Γλώσσα: | English |
| DOI: | 10.1093/gji/ggag234 |
| DOI: | 10.1093/gji/ggag234/68534792/ggag234.pdf |
| Διαθεσιμότητα: | https://doi.org/10.1093/gji/ggag234 https://academic.oup.com/gji/advance-article-pdf/doi/10.1093/gji/ggag234/68534792/ggag234.pdf https://academic.oup.com/gji/article-pdf/246/2/ggag234/68534792/ggag234.pdf |
| Rights: | https://creativecommons.org/licenses/by/4.0/ |
| Αριθμός Καταχώρησης: | edsbas.3FF2023E |
| Βάση Δεδομένων: | BASE |
| DOI: | 10.1093/gji/ggag234 |
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