Iterative intelligent high-precision high-SNR seismic weak reflection separation method and its application

Abstract The seismic facies-guided trace-by-trace high-precision seismic weak reflection separation method (SRSM) and the corresponding deep-learning seismic weak reflection separation method usually can obtain high-precision high-SNR (signal-to-noise ratio) seismic weak reflection separation results; however, they face great challenges when accounting for low-SNR seismic data, resulting in undesired low-precision low-SNR seismic weak reflection separation results. In this paper, in order to obtain high-precision high-SNR seismic weak reflection separation results, we propose an iterative intelligent high-precision high-SNR seismic weak reflection separation method (IIWSM) based on the SRSM and the multi-task deep-learning network. IIWSM consists of the iterative SRSM-based seismic weak reflection label automatic generation (IWLG), and the iterative multi-task high-precision high-SNR seismic weak reflection separation method (IMWSM). IWLG aims to generate the high-precision high-SNR seismic weak reflection label for IMWSM, and IMWSM aims to obtain high-precision high-SNR seismic weak reflection separation results. A synthetic 2D seismic data set and an actual 3D seismic data set example demonstrate that IIWSM can be used for high-precision high-SNR seismic weak reflection separation.