Matching in Curvelet Domain with L1 Norm Constrain

The traditional match filtering method is subject to many restrictions and is usually difficult to overcome the impact of noise. Based on the traditional match filter, we propose the curvelet domain L1 norm optimal matching filter. In this paper, two different types of seismic data are decomposed to the curvelet domain, different detailed effective information is extracted for L1-norm optimal matching, and ideal results are achieved. Based on the model test, we find that the L1 norm optimal matching filter attenuates the noise and the waveform, amplitude, and phase coherence of result signals are great.