EGU2020-12233
https://doi.org/10.5194/egusphere-egu2020-12233
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Constrained Surface-wave Dispersion Inversion Using GPR Reflection Data

Shufan Hu1, Yonghui Zhao1, Wenda Bi1, Ruiqing Shen1, Bo Li1, and Shuangcheng Ge2
Shufan Hu et al.
  • 1School of Ocean and Earth Science, Tongji University, Shanghai, China (zhaoyh@tongji.edu.cn)
  • 2Zhejiang University of Water Resources and Electric Power, Zhejiang, China

Ground penetrating radar (GPR) and Seismic Surface Wave methods (SWMs) are two nondestructive testing (NDT) methods commonly used in near-surface site investigations. These two methods investigate the media properties of subsurface based on different physical phenomena. GPR has a good resolvability to characterize the layered structure since the propagation of electromagnetic wave is sensitive to the change of electrical properties, while, the geometric dispersion of surface waves can be used to retrieve the variation of S-wave velocity (Vs) with depth. In most situations, these two data sets are processed separately, and the results are later used for comprehensive interpretation. Constrained inversion, as a way to implement data fusion, can alleviate the non-uniqueness of the solution and produce more consistent information for the comprehensive site and material investigations.

We present an algorithm for the inversion of surface-wave dispersion curves with GPR interface constraints in 2D media. The reflection interfaces interpreted from the GPR profile are integrated into a cell- and boundary-based Vs model. This implementation allows both vertical and lateral changes within each region while also allows sharp changes across the boundaries. In addition, our algorithm simultaneously inverts several dispersion curves extracted along the survey line using multi-size spatial windows, which mitigates the adverse effects of 1D assumption in traditional surface-wave dispersion inversion and improves the matching of GPR and SWMs in lateral variations. We use synthetic and field data sets to test the effectivity of the proposed method. Both results show the improved resolution of the Vs model retrieved by the constrained inversion compared to the standard inversion.

How to cite: Hu, S., Zhao, Y., Bi, W., Shen, R., Li, B., and Ge, S.: Constrained Surface-wave Dispersion Inversion Using GPR Reflection Data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12233, https://doi.org/10.5194/egusphere-egu2020-12233, 2020

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