University of Tehran Press Journal of the Earth and Space Physics 2538-371X 31 1 2005 03 21 - - 10865 FA Journal Article 1970 01 01 One of the main problems in geophysics data analysis is the presence of noise. This problem in seismic survey is more obvious than in the other branches. In this study the random noise suppression is presented by a filter which is called eigenimage filter and operates on stacked 3D seismic data in frequency domain. Our tools in suppression of random noises were SVD and Lanczos. The Lanczos method works much faster than SVD, specially when we have a sparse matrix. The special feature of the Lanczos method is its high performance. The F-xy filter has its own abilities such as fantastic signal preservation and well noise suppression, and can be used even before stacking. In this study presented performance of the filter on staked synthetic seismic data. One of the main problems in geophysics data analysis is the presence of noise. This problem in seismic survey is more obvious than in the other branches. In this study the random noise suppression is presented by a filter which is called eigenimage filter and operates on stacked 3D seismic data in frequency domain. Our tools in suppression of random noises were SVD and Lanczos. The Lanczos method works much faster than SVD, specially when we have a sparse matrix. The special feature of the Lanczos method is its high performance. The F-xy filter has its own abilities such as fantastic signal preservation and well noise suppression, and can be used even before stacking. In this study presented performance of the filter on staked synthetic seismic data. https://jesphys.ut.ac.ir/article_10865_7fbde3cae05db6928cec6bca67ec09d3.pdf