Data Mining and Knowledge Discovery Based on Denoising Algorithms in Geology Exploration

Abstract

There are mass data in geology exploration, but it is vital to find useful information or knowledge from these data. This paper is concerned with the analysis of the seismic data by the multi-channel wiener filter algorithm and the wavelet denoising method using neighboring coefficients. Known the velocity of reflection event, utilizes the resemblance of reflection signals in each seismic trace, the multi-channel wiener filter algorithm is effective in enhance reflection events and suppress the random noise. But the wavelet denoising methods don’t need any assuming conditions. The computed simulations of these two kinds of algorithms are provided to prove the availability.