A Fractal Conservation Law for Simultaneous Denoising and Enhancement of Seismic Data

In this letter, we have applied a new filtering method for the simultaneous noise reduction and enhancement of seismic signals using a fractal conservation law, which is simply a partial differential equation (PDE) modified by a nonlocal fractional antidiffusive term of lower order. By using an integral formula, which is based on Taylor-Poisson's formula and Fubini's theorem for an antidiffusive term, and then taking the fast Fourier transform of the PDE, the filter in the frequency domain can be derived. The study showed that this filter eliminates the high frequencies, amplifies the medium frequencies, and preserves the low frequencies. Thus, some features of the signal, such as relative maxima or minima, can be preserved or even amplified. Usually, these features are flattened by other denoising methods. The properties of this novel method are tested on both synthetic seismic data and real common shot point seismic records. Additionally, we compared this method with time-frequency peak filtering (TFPF), which has a good performance under low signal-to-noise ratio. The experimental results illustrate the superior performance of our method versus TFPF in the recovery of seismic events by removing random noise and enhancing valid signal.

[1]  Pascal Azerad,et al.  A non-monotone nonlocal conservation law for dune morphodynamics , 2010, Differential and Integral Equations.

[2]  Yue Li,et al.  Spatiotemporal Time–Frequency Peak Filtering Method for Seismic Random Noise Reduction , 2013, IEEE Geoscience and Remote Sensing Letters.

[3]  Hongbo Lin,et al.  Recovery of Seismic Events by Time-Frequency Peak Filtering , 2007, 2007 IEEE International Conference on Image Processing.

[4]  S. Cao,et al.  The second-generation wavelet transform and its application in denoising of seismic data , 2005 .

[5]  Yue Li,et al.  Parabolic-Trace Time-Frequency Peak Filtering for Seismic Random Noise Attenuation , 2014, IEEE Geoscience and Remote Sensing Letters.

[6]  Hongbo Lin,et al.  Suppression of strong random noise in seismic data by using time-frequency peak filtering , 2013, Science China Earth Sciences.

[7]  Wenkai Lu,et al.  Adaptive noise attenuation of seismic images based on singular value decomposition and texture direction detection , 2006 .

[8]  Mostefa Mesbah,et al.  Signal enhancement by time-frequency peak filtering , 2004, IEEE Transactions on Signal Processing.

[9]  P. E. Harris,et al.  Improving the performance of f-x prediction filtering at low signal-to-noise ratios , 1997 .

[10]  Ning Wu,et al.  Noise Attenuation for 2-D Seismic Data by Radial-Trace Time-Frequency Peak Filtering , 2011, IEEE Geoscience and Remote Sensing Letters.

[11]  Boualem Boashash,et al.  Time-frequency peak filtering applied to FSK signals , 1994, Proceedings of IEEE-SP International Symposium on Time- Frequency and Time-Scale Analysis.

[12]  Pascal Azerad,et al.  Simultaneous denoising and enhancement of signals by a fractal conservation law , 2010, 1004.5193.