Abstract: NCD ( Nonlinear Complex Diffusion) can adjust the diffusion intensity according to different structural features and effectively suppress the random noise in seismic data． However，the morphology of desert seismic data is complex，so that the NCD method is unable to effectively estimate the direction of the reflection event，leading to the attenuation of the reflection event． Aiming at this problem，an ASOCD ( Adaptive Structure-Oriented Complex Diffusion) algorithm is proposed based on the structural features of the reflection event．The oriented complex diffusion is performed along the direction of refection event to suppress the random noise and enhance the effective signal． And the proposed algorithm adaptively adjusts the diffusion threshold according
to the regional characteristics of seismic data，thus better recovers the seismic signal using a small diffusion threshold for the signal region． The results of the synthetic and real desert seismic data verify the effectiveness of the proposed method，and the proposed method can increase the SNＲ ( Signal-To-Noise Ｒatio) of filtered data by 6 dB more than the NCD method．

Key words: nonlinear complex diffusion ( NCD) , local covariance matrix, oriented complex diffusion, desert random nose, seismic exploration