Title :
Random-Noise Attenuation for Seismic Data by Local Parallel Radial-Trace TFPF
Author :
Mingjun Xiong ; Yue Li ; Ning Wu
Author_Institution :
Dept. of Inf., Jilin Univ., Changchun, China
Abstract :
Time-frequency peak filtering (TFPF) is a new and effective tool for random-noise attenuation in the time-frequency domain. The conventional TFPF processes each channel of the seismic record independently with a fixed window length (WL). However, different frequency signals have different optimal WLs. Obviously, a fixed WL cannot effectively attenuate random noise for all frequency components at the same time. Depending on the geometry of the reflection, we can assume that the moveout of the reflected event is locally linear. With this in mind and taking the spatial correlation of the reflection events between adjacent channels in different layers into account, we propose a novel approach which is to do the TFPF along the local direction of the reflection event instead of along the channel. This method is called the local parallel radial-trace TFPF. It not only has the advantage of TFPF in denoising but also reduces the sensitivity of WL, making the filtering more flexible and effective. Both the synthetic model and seismic data have proved its better performance in noise attenuation and effective component preservation.
Keywords :
geophysical techniques; random noise; seismology; time-frequency analysis; effective component preservation; fixed window length; frequency signals; local parallel radial-trace time-frequency peak filtering; optimal window lengths; random-noise attenuation; reflection events; seismic data; seismic record; spatial correlation; synthetic model; time-frequency domain; time-frequency peak filtering processes; Attenuation; Linearity; Noise reduction; Signal to noise ratio; Time-frequency analysis; Trajectory; Local parallel radial-trace time-frequency peak filtering (TFPF); radial-trace transform (RTT); random noise; seismic record processing; window length (WL);
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
DOI :
10.1109/TGRS.2013.2278981