Wavelet Transform In Seismic Signal Denoising

As an excellent mathematical analysis tool,Wavelet transform is being more and more important in engineering practice and replacing the role of the conventional Fourier transform in many research fields. Wave-let transform has received more and more concerns in signal processing field because of its capacity of analyzing the local information of signal in both time-domain and frequency-domain at the same time..De-noising of seismic data is a main task of geophysical exploration,improving the signal-to-noise radio is turning to more and more important accordingly.noises of seismic data mainly include coherent noises and random noises.Commonly there are some rules of coherent noises,so they can be removed according to their rules.Random noises have no rules,so it is difficult to remove random noises.Seismic data is no-steady signal,Wavelet transform processing no-steady signal has widely applied in many engineering field.The report is about the basic theory of wavelet transform and de-noise and its applying in signal processing,latterly combining with seismic data and noise of seismic data,particularly discuss de-seismic data as much as wavelet transform. Because characteristics of signal singularity differs from noise,the local maximas of wavelet transform modulus are different too and multiple analysis of wavelet transform.The module maximum of wavelet transform and threshold in de-noise are discussed mainly. The experiment show that performance of our methods is good and effectiveness.