EGU24-15474, updated on 09 Mar 2024
https://doi.org/10.5194/egusphere-egu24-15474
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Adaptive mesh joint inversion using seismic body and surface wave data: Method and Application

Ying Liu1, Hongjian Fang2, Huajian Yao1, and Haijiang Zhang1
Ying Liu et al.
  • 1School of Earth and Space Sciences, University of Science and Technology of China, Hefei, China
  • 2School of Earth Sciences and Engineering, Sun Yat‐sen University, Zhuhai, China

Seismic tomography using body or surface wave data is a powerful tool to explore the structure of Earth’s interior structure. In recent decades, joint inversion of seismic body and surface wave data has been widely employed to investigate seismic velocities of the Earth’s lithosphere and asthenosphere. Benefited from the complementary sensitivities of different datasets, seismic velocities determined by joint inversion generally exhibit higher resolution and accuracy. Regular mesh (cell or grid) is commonly used in seismic tomography. As data distribution is uneven in most cases, regularization techniques are implemented in regular mesh seismic tomography method to stabilize ill-posed problems. Despite the selection of appropriate regularization parameters, it is also challenging to achieve multiscale resolution in regular mesh joint inversion method. In this study, we developed a joint inversion method using adaptive irregular mesh according to the real data distribution based on Poisson-Voronoi cells. Synthetic tests show that the newly developed method can better resolve multi-scale structures without regularizations. We applied this method to a dataset with seismic arrays in different scales. The newly determined multiscale velocity model reveals distinct features particularly in areas with dense data distribution.

How to cite: Liu, Y., Fang, H., Yao, H., and Zhang, H.: Adaptive mesh joint inversion using seismic body and surface wave data: Method and Application, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15474, https://doi.org/10.5194/egusphere-egu24-15474, 2024.