In seismic exploration, the noise seriously distorts and interferes with seismic signal. Conventional methods of seismic data denoising can no longer meet the requirements of high-resolution seismic exploration. In this study, a method of seismic data denoising is proposed based on the shearlet transform, a new multi-scale transform with multi-directions, multi-resolutions, and optimal sparse approximation properties as well as high computational efficiency. The shearlet transform can get rid of random noise while retaining effective signals to the maximum degree, thereby effectively improving the signal-to-noise ratio. It is applied to synthetic and field seismic data with different signal-to-noise ratios, and compared with conventional methods of seismic data denoising. Results show that the shearlet transform is competitive in denoising applications in terms of both performance and computational efficiency.
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