Wavelet Transform Method Of Removal Of Surface Waves

Surface wave is a regular noise wave existing widely in seismic data. It can be defined as a group of events that contaminates seismic data by forming a high dip (low velocity) and high amplitude cone, which can dominate near-surface events on the seismic records, and it is normally found in land seismic surveys. However, it is the pivotal question in how to remove or pick-up this kind of noise in seismic data.With the appearance of high-density information collection equipment and improvement of the request of the explanation precision, traditional explanation cannot reach the request of practical production. The wavelet transform is a new branch of mathematics. It is a method of time-scale (time-frequency), which has multi-resolution characteristics. So this characteristic making Wavelet Transform becomes a powerful tool in removing or picking up surface wave.Above all, on the plat of MATLAB wavelet function toolbox, in this paper, we use two-dimension wavelet transforms decompose theory models and practical data in as many levels an necessary, analyze the coefficients and identify the regions where the ground roll appears, then select the regions affected by the noise in order to apply a muting in the coefficients located in these regions, in the end reconstruct the signal with the new set of coefficients which has impact result. Compared with other methods, this method has the advantages of high accuracy, small distortion and quick calculation. After the imaging system brought forward by this thesis being optimized, it can be directly used in the practical work. This kind of method has special value in seismic data.