Applying Nonlinear Diffusion To Seismic Image Sequences

Seismic signal denoising can increase seismic image's signal to noise ratio. It makes the indispensable event of seismic interpretation and its reflective important geologic framework getting enhanced. It also lays a good foundation for accurate geologic structure interpretation. It provides reliable basis for setting the well. It has important and realistic significance to oilfield development. Seismic signal denoising is the difficulty and hotspot of signal processing domain. Carrying on the research of this aspect, not only has important and realistic significance to account for exploratory and development of petroleum and gas, but also can huge accelerate the development of the rest domanial investigate of signal denoise. Basing on this feature to calculate, the article researches of denoise of seismic exploration, primaryly explores the method of nonlinear filtering based on partial differential equation.The article roots in higher education institutions mainstay inaugurating item"Investigate the nonlinear coherence enhancing diffusion technology to seismic image sequences".This article first briefly introduces the seismic survey's principle, production work, terminology explanation and signal noise's source and classify. And then the article educes image denoising's significant sense to seismic interpretation. Therefore, it results in nonlinear filtering methods and introduce its developing process, principium of denoise. Then analyses the traditional nonlinear filtering--median filtering and the denoising method based on partial differential equation. Aiming at the advantages and disadvantages of them, each algorithm is ameliorated. As a result of the algorithm of coherence enhancing diffusion can boost up linear texture's border. It not only effectively removes noise but also can boost up the events. It can apply for seismic image. The result of estimating the SNR of handled images indicated that the algorithm can acquire favorable effects for denoising seismic signal and boost the quality of the seismic data. The result of applying the algorithm for filtering the seismic section is good. The research indicates the seismic signal processing method which based on partial differential equation is advisable. While the partial differential equation has the advantages of simpleness, rapidness and apting to concurrent processing. It has the prospect of application.