Research And Application Of Seismic Data Denoising Method Based On Curvelet Transform

Now the face of the increasingly complex exploration environment,in the past in the plains,and now more in the mountains or desert areas,exploration and diverse technologies,including seismic exploration in many exploration methods used the most and most extensive exploration method.Facing the complex exploration environment,seismic exploration is also developing and deepening.The continuous deterioration of the environment will produce more complex information in the seismic exploration process,which contains information that reflects the underground structure and lithology,but also contains a variety of noise,in order to be able to understand the underground structure of the information and rock Information,which requires us to constantly increase the signal-to-noise ratio of the collected information,so that the interpreter can be more clearly on the underground geological structure to make a better analysis.Due to the increasing demand for SNR of seismic data,it is one of the indispensable technologies to improve the signal-to-noise ratio of seismic data.In this paper,we mainly introduce the noise in seismic exploration,and analyze the causes of it and briefly introduce the basic methods of denoising.The noise of seismic data is denoised by wavelet transform denoising method.Synthetic record and actual seismic Data are used to verify the denoising effect.At the same time,the Curvelet transform denoising method is used to denoise the synthetic records and the actual seismic data and compare with the wavelet transform denoising effect to analyze the advantages of the Curvelet transform denoising method.This paper focuses on the principle of Curvelet transform and several denoising methods,including: based on conventional Curvelet transform threshold denoising method,based on the second generation Curvelet transform threshold adaptive denoising method and KL transform and Curvelet transform combined denoising method,These methods compared to the traditional method of denoising in many ways have greatly improved,have achieved very good results,can effectively improve the seismic data SNR,which for the follow-up explanation and further processing to provide a better According to the results of synthetic records and actual data processing,the denoising method based on Curvelet transform method is more stable,efficient and near optimal for traditional denoising methods.