Full waveform inversion based on morphological component analysis seismic data reconstruction

Abstract

Seismic exploration is the most important and the most effective method of solving the petroleum exploration problem which uses seismic data to cognize the underground geological structure and orientate oil and gas traps. Full waveform inversion (FWI) could build precision velocity model of earth medium through the extraction of the full information content of the seismic data. The quality of seismic data has significant impact on the full waveform inversion. However, field seismic data acquisition is restricted by various conditions, the observation system is often irregular, seismic data may be missing. Irregularity or missing of seismic data will seriously affect the seismic processing and interpretation results. Seismic data reconstruction methods can be used to restore the missing data, then improve the quality of seismic data. In this paper, we utilize the morphological component analysis (MCA) method to reconstruct the seismic data. Then we combine this method with full waveform inversion to provide high quality seismic data which used as input for FWI. Experimental results show that not only can the MCA method rebuild seismic data accurately but also has the effect of denoising. Full waveform inversion based on MCA seismic data reconstruction can obtain higher precision subsurface velocity. We apply this method to the field seismic data, the quality of seismic data is improved, and can obtain better inversion results.