Seismic Signal Denoising Method Based On The Radon Transform High-density Point For Research

Seismic exploration in the FK domain filtering rules are frequently used to suppress interference, several times with random noise superimposed thought suppression; but the two methods at low SNR and strong interference rules have limitations. Effect is not very satisfactory. For the seismic disturbance, this paper focuses on the elimination of surface waves.Light source, the surface wave will be directly from the boundary between earth and air. Surface wave propagation velocity smaller than the wave, its frequency is low, the energy in the vertical, horizontal direction can be attenuated, but the slow decay on the horizontal direction, continuing a long time. Seismic profiles, surface wave and the performance of a broom-shaped dispersion. Nearly offset by strong interference from the reflected wave, the wave energy quilt annihilation. Although collected in the field using a surface wave suppression measures, but the records collected in the surface wave interference persists, affect the processing and interpretation of results.This paper discusses the Radon transform of the relevant knowledge, on the Radon transform in-depth analysis and research. Using a linear Radon transform, parabolic Radon transform of the same surface wave seismic data to eliminate, the result is the elimination of the linear effect of the Radon transform is better than the parabolic Radon transform.Followed the Radon transform in the frequency domain complex matrix algorithm, by the Fourier transform, all the matrices are transformed into the frequency domain, the use of the Gauss-Jol was elected principal component inversion method, because of the time complexity is the dimension of the cubic matrix, for large matrices, the long running time. In this paper, parallel algorithms for Gauss-Jol was elected principal component inversion method to improve the time dimension of complexity into the square of the matrix, and achieved good results very well.Finally, we discuss high-density point of seismic acquisition, analysis of the current seismic data acquisition using high-density point of need.