Low-Frequency Compensation of Seismic Data Based on Compressed Sensing
Y. Ding, Q. Du, L. Liu and L. Fu
Event name: 81st EAGE Conference and Exhibition 2019
Session: Poster: Signal Processing B
Publication date: 03 June 2019
Info: Extended abstract, PDF ( 503.83Kb )
Price: € 20
Complex subtle reservoirs have become the main geological exploration targets, which require higher resolution of seismic data. Loss of low-frequency information is one of the dominant reasons for the data with poor quality. In this paper, we apply compressed sensing theory on the low-frequency compensation of seismic data. Based on the sparsity of reflection coefficient, the fast iterative shrinkage threshold algorithm (FISTA) is first utilized to the inversion of reflection coefficient, which enhances the convergence speed and the calculation efficiency. Furthermore, we design an improved broadband low-pass filter to compensate the low-frequency seismic signal, which solves the distortion of spectral superposition signal. The proposed algorithm is tested with real seismic data, and the results show that low frequency below 10 Hz can be effectively compensated, contributing to superior resolution of reflection events and improved image quality of weak signal.