TY - GEN
T1 - Random noise attenuation for seismic data by multiscale time-frequency peak filtering via nonsubsampled pyramid
AU - Zhang, C.
AU - Li, Y.
AU - Lin, H. B.
AU - Yang, B. J.
AU - Deng, X. Y.
PY - 2014
Y1 - 2014
N2 - Time-Frequency Peak Filtering (TFPF) is an effective method to eliminate pervasive random noise when seismic signals are analyzed. TFPF can give an unbiased estimation in case that the signal is linear. In general, we use pseudo Wigner-Ville distribution (PWVD) to realize the local linearity. However, there is a pair of contradiction in this method. If we choose a short window length (WL) for PWVD in the TFPF, it leads to good preservation for signal amplitude, but the denoising performance is relatively poor. So a fixed WL cannot solve the contradiction between the noise attenuation and signal preservation. To solve the problem, we adopt a nonsubsampled pyramid (NSP) to decompose the seismic data into multiscale components from low to high frequency. Then we can apply a short WL in signal-dominant scale to preserve the signal and a long WL is chosen for noise-dominant scale by the TFPF to eliminate more noise. We test the performance of our new method on both synthetic and real seismic data. According to the results, the Multiscale TFPF based on nonsubsampled pyramid can more effectively improve the signal-to-noise ratio and preserve events better than conventional TFPF.
AB - Time-Frequency Peak Filtering (TFPF) is an effective method to eliminate pervasive random noise when seismic signals are analyzed. TFPF can give an unbiased estimation in case that the signal is linear. In general, we use pseudo Wigner-Ville distribution (PWVD) to realize the local linearity. However, there is a pair of contradiction in this method. If we choose a short window length (WL) for PWVD in the TFPF, it leads to good preservation for signal amplitude, but the denoising performance is relatively poor. So a fixed WL cannot solve the contradiction between the noise attenuation and signal preservation. To solve the problem, we adopt a nonsubsampled pyramid (NSP) to decompose the seismic data into multiscale components from low to high frequency. Then we can apply a short WL in signal-dominant scale to preserve the signal and a long WL is chosen for noise-dominant scale by the TFPF to eliminate more noise. We test the performance of our new method on both synthetic and real seismic data. According to the results, the Multiscale TFPF based on nonsubsampled pyramid can more effectively improve the signal-to-noise ratio and preserve events better than conventional TFPF.
UR - http://www.scopus.com/inward/record.url?scp=84907416507&partnerID=8YFLogxK
U2 - 10.3997/2214-4609.20141580
DO - 10.3997/2214-4609.20141580
M3 - Conference contribution
AN - SCOPUS:84907416507
SN - 9781632666949
T3 - 76th European Association of Geoscientists and Engineers Conference and Exhibition 2014: Experience the Energy - Incorporating SPE EUROPEC 2014
SP - 1206
EP - 1210
BT - 76th European Association of Geoscientists and Engineers Conference and Exhibition 2014
PB - EAGE Publishing BV
T2 - 76th European Association of Geoscientists and Engineers Conference and Exhibition 2014: Experience the Energy - Incorporating SPE EUROPEC 2014
Y2 - 16 June 2014 through 19 June 2014
ER -