Seismic data random noise attenuation based on the second generation Curvelet transform

Noise attenuation of seismic data processing is one of the key questions that can not be ignored.According to the nonlinear approximation property of the Curvelet transform in objects with piecewise C₂ edges,a threshold method of random noise attenuation in seismic data is proposed based on the Curvelet transform.And an estimation approach of the threshold value is presented on the assumption that the random noise is independent and identically distributed Gaussian white noise.The synthetic data and post-stack real data processing results confirm the effectiveness of the proposed method.