Noise suppression algorithm for seismic data based on SSEC-EWT
MENG Juan1,2, GAO Qin1, LI Ya'nan1,2
1. School of Electronic Science and Control Engineering, Institute of Disaster Prevention, Sanhe, Hebei 065201, China; 2. Hebei Key Laboratory of Seismic Disaster Ins-trument and Monitoring Technology, Sanhe, Hebei 065201, China
Abstract：Seismic exploration data with high a signal-to-noise ratio is a solid basis for oil and gas exploration. Most existing de-noising methods cannot suppress the ubiquitous ground roll and random noise in seismic data at the same time and can easily damage the effective wave. In this regard, we proposed a noise suppression algorithm for seismic data, which was based on the S-transform spectrum energy curve (SSEC) and empirical wavelet transform (EWT). Firstly, seismic records were processed by S-transform, and the energy of each frequency point was calculated according to the S-spectrum. Secondly, the maximum point frequency of the energy curve and the ε-neighborhood method were used to determine the spectral segmentation boundary to improve the traditional EWT. Thirdly, the intrinsic mode function (IMF) of the ground roll was determined according to the SSEC, and a band-pass filter was constructed to filter the ground roll IMF to protect the effective wave and achieve accurate ground roll suppression. Finally, dominant frequencies of the remaining IMF were calculated, and the random noise IMF was removed according to the frequency threshold of the effective wave to obtain the denoised record. The simulation test shows that the improved EWT can decompose the seismic signal adaptively according to frequency and energy, thereby separating the ground roll and random noise accurately. Especially in a strong noise environment, the proposed algorithm can separate ground roll and random noise accurately and synchronously. The processing results of actual seismic data reveal that the algorithm can protect the effective wave while suppressing the ground roll and random noise, thus improving the signal-to-noise ratio of the seismic data.
Ma J, Li Q.Ground roll suppression with joint S transform and TT transform[J]. Procedia Earth & Planetary Science, 2011, 33(3):246-252.
[2]
徐阳, 罗明璋, 王智, 等.广义S变换与二维离散小波变换联合压制面波[J]. 石油物探, 2018, 57(3):395-403.XU Yang, LUO Mingzhang, WANG Zhi, et al. Surface wave suppression using generalized S-transform and 2D discrete wavelet transform[J]. Geophysical Prospecting for Petroleum, 2018, 57(3):395-403.
[3]
Li J H, Ma J Q.Seismic ground roll suppression based on the generalized S transform[J]. International Journal of Digital Content Technology and Its Applications, 2013, 7(7):554-560.
[4]
董烈乾, 李振春, 王德营, 等.第二代Curvelet变换压制面波方法[J]. 石油地球物理勘探, 2011, 46(6):897-904.DONG Lieqian, LI Zhenchun, WANG Deying, et al.Ground-roll suppression based on second generation Curvelet transform[J]. Oil Geophysical Prospecting, 2011, 46(6):897-904.
[5]
李继伟, 刘晓兵, 周俊骅, 等.基于能量比的Curvelet阈值迭代面波压制[J]. 石油地球物理勘探, 2019, 54(5):997-1004.LI Jiwei, LIU Xiaobing, ZHOU Junhua, et al.A curvelet threshold iteration method based on energy ratio for surface-wave suppression[J]. Oil Geophysical Prospecting, 2019, 54(5):997-1004.
[6]
Liu Z, Chen Y K, Ma J W.Ground roll attenuation by synchrosqueezed curvelet transform[J]. Journal of Applied Geophysics, 2018, 151:246-262.
[7]
曾祥堃, 乔宝平, 刘依谋, 等.基于小波变换的自适应面波压制方法[J]. 北京大学学报(自然科学版), 2015, 51(5):837-842.ZENG Xiangkun, QIAO Baoping, LIU Yimou, et al.Adaptive ground roll attenuation based on the wavelet transform[J]. Acta Scientiarum Naturalium Universitatis Pekinensis (Natural Science Edition), 2015, 51(5):837-842.
[8]
董烈乾, 李振春, 杨少春, 等.基于经验模态分解的f-x域面波压制方法[J]. 石油地球物理勘探, 2013, 48(1):42-48.DONG Lieqian, LI Zhenchun, YANG Shaochun, et al.Ground roll suppression in f-x domain based on empirical mode decomposition[J]. Oil Geophysical Prospecting, 2013, 48(1):42-48.
[9]
Chen W, Xie J, Zu S, et al.Multiple-reflection noise attenuation using adaptive randomized-order empirical mode decomposition[J]. IEEE Geoscience and Remote Sensing Letters, 2017, 1(14):18-22.
[10]
Golestani A, Kolbadi S S, Heshmati A A.Localization and de-noising seismic signals on SASW measurement by wavelet transform[J]. Journal of Applied Geophysics, 2013, 98:124-133.
[11]
李海山, 陈德武, 吴杰, 等.叠前随机噪声深度残差网络压制方法[J]. 石油地球物理勘探, 2020, 55(3):493-503.LI Haishan, CHEN Dewu, WU Jie, et al.Pre-stack random noise suppression with deep residual network[J]. Oil Geophysical Prospecting, 2020, 55(3):493-503.
[12]
Gilles J.Empirical wavelet transform[J]. IEEE Transactions on Signal Processing, 2013, 61(16):3999-4010.
[13]
王秋生, 陈璐, 袁海文, 等.基于经验小波变换的电晕电流降噪方法[J]. 电网技术, 2017, 41(2):670-676.WANG Qiusheng, CHEN Lu, YUAN Haiwen, et al.Corona current de-noising method based on empirical wavelet transform[J]. Power System Technology, 2017, 41(2):670-676.
[14]
吕跃刚, 何洋洋.EWT和ICA联合降噪在轴承故障诊断中的应用[J]. 振动与冲击, 2019, 38(16):42-48.LYU Yuegang, HE Yangyang.Application of an EWT-ICA combined method in fault diagnosis of rolling bearings[J]. Journal of Vibration and Shock, 2019, 38(16):42-48.
[15]
Chegini S N, Bagheri A, Najafi F. Application of a new EWT-based de-noising technique in bearing fault diagnosis[J]. Measurement, 2019, 144(5):275-297.
[16]
Liu W, Cao Y.Seismic Time-Frequency Analysis via Empirical Wavelet Transform[J] IEEE Geoscience and Remote Sensing Letters, 2016, 1(13):28-32.
[17]
Hui C, Kang J, Chen Y, et al.An improved time-frequency analysis method for hydrocarbon detection based on EWT and SET[J]. Energies, 2017, 10(8):1090.
[18]
覃发兵, 徐振旺, 啜晓宇, 等.基于经验小波变换的地震资料噪声压制方法[J]. 中国石油勘探, 2018, 23(5):100-110.QIN Fabing, XU Zhenwang, CHUAN Xiaoyu, et al.Seismic noise suppression based on empirical wavelet transformation[J]. China Petroleum Exploration, 2018, 23(5):100-110.
[19]
Chen W, Song H.Automatic noise attenuation based on clustering and empirical wavelet transform[J]. Journal of Applied Geophysics, 2018, 159:649-665.
[20]
Liu N, Li Z, Sun F, et al.The improved empirical wavelet transform and applications to seismic reflection data[J]. IEEE Geoscience and Remote Sensing Letters, 2020, 17(6):1103-1103.
[21]
孟娟, 韩智明, 高琴, 等.基于小波谱能量曲线EWT的面波压制算法[J]. 地球物理学进展, 2021, 36(4):1581-1589.MENG Juan, HAN Zhiming, GAO Qin, et al.An seismic surface wave suppression algorithm based on wavelet spectrum energy curve EWT[J]. Progress in Geophysics, 2021, 36(4):1581-1589.
[22]
Liu Z D, Lu Q T, Dong S X, et al.Research on velocity and acceleration geophones and their acquired information[J]. Applied Geophysics, 2012, 9(2):149-158.
