Application of full-waveform inversion to low-Frequency reconstruction algorithm

Full-waveform inversion (FWI) is a nonlinear optimization technique that allows the extraction of subsurface property information from seismic data. In full-waveform inversion, low-frequency is essential for extracting long-wavelength features and appropriate subsurface properties. However, low-frequency in seismic data obtained in the field are often contaminated by various noises and are typically removed using high-pass filters. Low-frequency provides structural information necessary for constructing a background velocity model and are crucial in preventing full-waveform inversion results from converging to local minimum instead of the global minimum. Furthermore, the lack of low-frequency components in the data can lead to cycle skipping problems, which mostly causes the inaccurate retrieval of long-scale features. Various studies have been conducted to address the absence of low-frequency components in full-waveform inversion. Chen et al.(2019) extracted low-frequency information related to the long-wavelength components of the subsurface using the multiscale envelope of seismic data. Na et al.(2024) proposed an algorithm for low-frequency reconstruction based on recurrent neural networks. The proposed algorithm was shown to accurately reconstruct the low-frequency components of seismic data. In this study, full-waveform inversion was applied to the data with the reconstructed low-frequency. In numerical test, modified Overthrust model was utilized to generate the synthetic observed data. A Ricker wavelet with a dominant frequency of 8Hz was utilized as the source wavelet, and a Butterworth filter with a cutoff frequency of 8Hz were applied to generate data with removed low-frequency components. Finally the inversion results for both data with and without reconstructed low-frequency components were compared.

 

Acknowledgments

This research was supported by Korea Institute of Marine Science & Technology Promotion (KIMST) funded by the Ministry of Oceans and Fisheries, Korea (RS-2023-00259633).