Time-varying spectral modeling deconvolution based on synchrosqueezed wavelet transform to improve seismic data resolution

Zhang, Yan (China University of Petroleum–East China) | Li, Zhenchun (China University of Petroleum–East China) | Wang, Jiao (China University of Petroleum–East China)

OnePetro 

Due to the absorption of the formation, the frequency band of seismic wave narrows in the process of propagation and the resolution decreases. Spectral modelling deconvolution improves the resolution of seismic data by fitting the wavelet amplitude spectrum and applying zero-phase deconvolution on the seismic signal. Considering the different frequency components of seismic data from different depths, compensating the spectrum differently according to the depth of seismic data is meaningful, in which the time-frequency spectrum is needed. Recently proposed time-frequency analysis method named Synchrosqueezed Wavelet Transform (SSWT) is superior to the traditional time-frequency analysis method in time-frequency resolution, which has been applied to seismic data processing and interpretation. In this paper, we propose a method named Time-Varying Spectral Modeling Deconvolution Based on SSWT and apply it to seismic data to improve the resolution. The effectiveness of the proposed method in improving the resolution is verified by testing field data and comparing it with the results based on Generalized S-transform.

Presentation Date: Thursday, September 28, 2017

Start Time: 9:45 AM

Location: 340A

Presentation Type: ORAL