Abstract
We present a data-driven dispersion curve inversion network (DispINet) that directly maps the multimode dispersion curves to the S-wave velocity model. DispINet is trained with synthetic samples that consist of multimode dispersion curve data and the corresponding S-wave velocity models. The S-wave velocity models are generated according to prior information in a specific study area. Multimode dispersion curves are calculated by the generalized reflection-transmission coefficient method for each model. The well-trained DispINet could be used to predict the S-wave velocity model for other dispersion curve data never seen by DispINet. Testing data and Qademah field data results show that DispINet has the ability to retrieve a reasonable underground S-wave velocity structure in real time.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 104430 |
| Journal | Journal of Applied Geophysics |
| Volume | 193 |
| DOIs | |
| State | Published - Jul 28 2021 |
| Externally published | Yes |
Bibliographical note
KAUST Repository Item: Exported on 2021-08-23Acknowledgements: This research was partially supported by the National Natural Science Foundation of China (Grant Nos. 41974044, U1901602, and 41790465). We thank the subsurface imaging and fluid modeling (CSIM) group at KAUST for providing the Qademah field data.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.
ASJC Scopus subject areas
- Geophysics