Coal Geology & Exploration


There are two problems in the random noise attenuation in f-x domain:(1) Reflected waves as hyperbolic events in pre-stack CMP gather or shot gathers, de-noising will damage the effective wave; (2) Seismic signals are complex non-stationary signals, requiring that the de-noising method has the adaptivity. Aiming at these two problems, a random noise suppression method based on f-x EEMD was proposed. The method utilizes the reflected waves which are horizontal events in common offset gathers, satisfying the f-x domain de-noising assumption, and the good adaptability of EEMD algorithm to non-stationary signals. For each frequency slices in the f-x domain, signal is decomposed into a series of IMFs by EEMD, and the first IMF component which is noise dominant is removed. Finally, f-x domain data is inversely transformed back to t-x domain to realize noise separation. The theoretical trial and practical application indicate that the proposed method can suppress the random noise while maintaining the desired signal.


random noise, common offset gather, f-x domain, EEMD, noise surpression




[1] LIU Zhiping,CHEN Xiongbo,LI Jingye. Noncausal spatial prediction filtering based on an ARMA model[J]. Applied Geophysics,2009,6(2):122-128.

[2] CANALES L L. Random noise reduction[C]//Seg Technical Program Expanded Abstracts.Atlanta:SEG,1984.

[3] 国九英,周兴元,杨慧珠. 三维f-x,y 域随机噪音衰减[J]. 石油地球物理勘探,1995,30(2):207-215. GUO Jiuying,ZHOU Xingyuan,YANG Huizhu. Attenuation of random noise in(f-x,y) domain[J]. Oil Geophysical Prospecting, 1995,30(2):207-215.

[4] CHEN Y,MA J. Random noise attenuation by f-x empirical-mode decomposition predictive filtering[J]. Geophysics, 2013,79(3):81-91.

[5] 苏贵士,周兴元,李承楚. 频率空间(三维)F-XYZ域预测去噪技术[J]. 石油地球物理勘探,1998,33(1):95-104. SU Guishi,ZHOU Xingyuan,LI Chengchu.Prediction of noise elimination in F-XYZ domain[J]. Oil Geophysical Prospecting, 1998,33(1):95-104.

[6] 康冶,于承业,贾卧,等.F-x 域去噪方法研究[J]. 石油地球物理勘探,2003,38(2):136-138. KANG Ye, YU Chengye, JIA Wo, et al. A study on noise-suppression method in f-x domain[J]. Oil Geophysical Prospecting,2003,38(2):136-138.

[7] BEKARA M,VAN DER BAAN M. Random and coherent noise attenuation by empirical mode decomposition[J]. Geophysics, 2008,74(5):89-98.

[8] CAI Hanpeng,HE Zhenhua,HUANG Deji. Seismic data denoising based on mixed time-frequency methods[J]. Applied Geophysics,2011,8(4):319-327.

[9] CHEN Yangkang,GAN Shuwei,LIU Tingting,et al. Random noise attenuation by a selective hybrid approach using f-x empirical mode decomposition[J]. Journal of Geophysics & Engineering,2015,12(1):12-25.

[10] HUANG N E,SHEN Z,LONG S R,et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J]. Proceedings of the Royal Society A:Mathematical Physical & Engineering Sciences, 1998,454:903-995.

[11] RILLING G,FLANDRIN P,GONCALVES P. On empirical mode decomposition and its algorithms[C]//In Proceedings of IEEE-EURASIP Workshop on Nonlinear Signal and Image Processing NSIP-03,Grado,2003.

[12] LIU Yanping,LI Yue,LIN Hongbo,et al. An amplitude-preserved time-frequency peak filtering based on empirical mode decomposition for seismic random noise reduction[J]. IEEE Geoscience & Remote Sensing Letters,2014,11(5):896-900.

[13] WU Zhaohua,HUANG Norden E. Ensemble empirical mode decomposition:A noise-assisted data analysis method[J]. Advances in Adaptive Data Analysis,2009,1(1):1-41.

[14] WANG Y H,YEH C H,VINCENT YOUNG H W,et al. On the computational complexity of the empirical mode decomposition algorithm[J]. Physica A:Statistical Mechanics & Its Applications,2014,400:159-167.

[15] FU Yanxiao,JIA Limin,QIN Yong,et al. Fast EEMD based AM-correntropy matrix and its application on roller bearing fault diagnosis[J]. Entropy,2016,18(7):242.

[16] 黄海波,黄晓蓉,苏瑞强,等. 基于EEMD与GA-小波神经网络的传动系声品质预测[J]. 振动与冲击,2017,36(9):130-137. HUANG Haibo,HUANG Xiaorong,SU Ruiqiang,et al. Prediction of power train sound metric based on ensemble empirical mode decomposition and GA-Wavelet neural network[J]. Journal of Vibration and Shock,2017,36(9):130-137.

[17] GÓMEZ J L,VELIS D R. A fast empirical mode decomposition for noise attenuation of seismic data[C]//Seg Technical Program Expanded. New Orleans:Society of Exploration Geophysicists, 2015.

[18] WU W,PENG H. Application of EMD denoising approach in noisy blind source separation[J]. Journal of Communications, 2014,9(6):506-514.



To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.