| Seismic data is a complex nonlinear nonstationary signal,which is a reflection signal from geosphere collected by motivating the earthquake artificially in the process of oil and gas explorations.The purpose of seismic exploration is to image the seismic data and to find the underground oil and gas reservoirs through the distribution of reflectivity.It is more and more necessary to improve the seismic data processing technology to find effective seismic data to improve the efficiency of exploitation.So this paper studies denoising of the random noise and three-dimensional visualization of seismic signal.Because of the complex geological structure,the surface environment and the interference of exploration instruments,the collected seismic data contain a lot of noise signals,even cover the effective seismic signals.The object of this paper researchs is irregular random noise.Because of the complex factors such as the wide frequency domain and many causes of the noises,the existing random noise suppression algorithms have many disadvantages.In this paper,the empirical wavelet transform(EWT)proposed in recent years is studied.The algorithm based on the empirical spectrum boundary detection constructs a wavelet filter bank,and decomposes the signal into multiple modes.The detection method uses the clustering of spectral scale space.The signal adaptive representation algorithm,which is similar to the empirical wavelet transform is empirical mode decomposition(EMD).However,EMD algorithm can cause modal aliasing and envelope fitting error in some signal’s mode decomposition.This is the first time that EWT is applied to the 2D seismic data denoising,and compared the effect of suppressing the random noise in 2D seismic data with the empirical mode decomposition(EMD)and complete ensemble empirical mode decomposition(CEEMD)and classical wavelet transform denoising algorithm which are similar to empirical wavelet transform(EWT).The results of experiments show that two dimensional EWT combines with adaptive threshold denoising algorithm has the greatest signal-to-noise ratio and the least mean square error after denoising of the common shot trace set of two dimensional seismic data.The 3D visualization of data use the computer graphics display the data features directly and clearly.Three dimensional seismic data is usually used for interpretation works,but because of data storage structure of the SEGY format which is an open and general seismic data format,the speed of reading a seismic data volume which occupys more than a dozen GB memory space will be very slow.This paper based on the Open Inventor which is object oriented 3D visualization Library researches and constructs index grid of horizon data,and renders horizon data which is ups and downs in three-dimensional space.The processing mode of the volume data is also studied.The large data management(LDM)file format with multi-resolution data visualization,in which the data is stored in the octree structure to adapt to memory and performance.The data encoding method can realize effective random access,and the use multi thread asynchronous data loading.Not only the interaction of large scale seismic data visualization is very well,the resolution of image is high.Finally,the data before and after the denoising show in the three-dimensional visualization system and the denoising seismic data drawn with MATLAB are compared. |
