Discussions on the Processing of the Multi-Component Seismic Vector Field
Abstract
:1. Introduction
2. Multi-Component De-Noising Methods with Respect to the Vector Seismic Field
2.1. The Polarization Filtering Method
2.2. The Vector Wavefield Filtering Method Based on Vector Order Statistics
2.3. Multi-Component Joint De-Noising Based on the Group Sparsity Representation
2.4. The Vector Separating Method of the P-wave and S-wave
3. Suggestion
4. Conclusions and Perspectives
Author Contributions
Funding
Conflicts of Interest
References
- Mohammed, F.; Wang, J.Y. A review on multicomponent seismology: A potential seismic application for reservoir characterization. J. Adv. Res. 2016, 7, 515–524. [Google Scholar]
- Barkved, O.; Bartman, B.; Gaiser, J.; Van Dok, R.; Johns, T.; Kristiansen, P.; Probert, T.; Thompson, M. The many facets of multicomponent seismic data. Oilfield Rev. 2004, 16, 42–56. [Google Scholar]
- Crampin, S.; Peacock, S. A review of the current understanding of seismic shear-wave splitting in the Earth’s crust and common fallacies in interpretation. Wave Motion 2008, 45, 675–722. [Google Scholar] [CrossRef]
- Johnson, P.A.; Rasolofosaon, P.N.J. Nonlinear elasticity and stress-induced anisotropy in rock. J. Geophys. Res. Solid Earth 1996, 101, 3113–3124. [Google Scholar] [CrossRef]
- Sun, Q.F.; Du, Q.Z. A review of the multi-component seismic data processing. Pet. Explor. Dev. 2011, 38, 67–73. [Google Scholar]
- Tong, P.; Zhao, D.; Yang, D. Tomography of the 2011 Iwaki earthquake (M 7.0) and Fukushima nuclear power plant area. Solid Earth 2012, 3, 43–51. [Google Scholar] [CrossRef]
- Wu, H.; Chen, J.; Huang, X.Y.; Yang, D.H. A New Earthquake Location Method Based on the Waveform Inversion. Commun. Comput. Phys. 2018, 23, 118–141. [Google Scholar] [CrossRef]
- Crampin, S.; Gao, Y. A review of techniques for measuring shear-wave splitting above small earthquakes. Phys. Earth Planet. Inter. 2006, 159, 1–14. [Google Scholar] [CrossRef]
- Zhang, Y.G.; Wang, Y.; Wang, M.Y. Some Key Problems in the Multi-Component Seismic Exploration. J. Geophys. 2004, 47, 151–155. [Google Scholar]
- Zhao, B.; Wang, Y.; Lu, J. New progress and key problems in multicomponent seismic exploration technology. Oil Geophys. Prospect. 2012, 47, 506–516. [Google Scholar]
- Chen, H.; Yin, X.; Gao, J.; Liu, B.; Zhang, G. Seismic inversion for underground fractures detection based on effective anisotropy and fluid substitution. Sci. China Earth Sci. 2015, 58, 805–814. [Google Scholar] [CrossRef]
- Yin, X.Y.; Zong, Z.Y.; Wu, G.C. Research on seismic fluid identification driven by rock physics. Sci. China Earth Sci. 2015, 45, 8–21. [Google Scholar] [CrossRef]
- Lei, J. Impact of anisotropic and inhomogeneous medium on measuring seismic shear-wave splitting. Chin. Sci. Bull. 2017, 62, 2619–2629. [Google Scholar] [CrossRef]
- Wang, Y.; Yang, D.H.; Yin, C.C.; Gao, Y. Anisotropic geophysics and vector field. Chin. Sci. Bull. 2017, 62, 2595–2605. [Google Scholar] [CrossRef]
- An, S.P.; Hu, T.Y. Suppression of seismic surface waves based on adaptive weighted super-virtual interferometry. Sci. China Earth Sci. 2016, 46, 1371–1380. [Google Scholar] [CrossRef]
- Li, Y.; Yang, B.; Lin, H.; Ma, H.; Nie, P. Suppression of strong random noise in seismic data by using time-frequency peak filtering. Sci. China Earth Sci. 2013, 43, 1123–1131. [Google Scholar] [CrossRef]
- Zhao, B.L.; Shi, Y.M.; Yao, F.C.; Niu, Y.L.; Jiang, Y.; Chen, Z.D.; Wang, G.S.; Ma, X.Y. Prediction of the remaining oil distribution using multi-component seismic full waveform elastic inversion. Acta Pet. Sin. 2013, 34, 328–333. [Google Scholar]
- Kamath, N.; Tsvankin, I. Elastic full-waveform inversion for VTI media: Methodology and sensitivity analysis. Geophysics 2016, 81, C53–C68. [Google Scholar] [CrossRef]
- Zhang, Q.; McMechan, G.A. 2D and 3D elastic wavefield vector decomposition in the wavenumber domain for VTI media. Geophysics 2010, 75, D13–D26. [Google Scholar] [CrossRef]
- Wang, W.L.; McMechan, G.A.; Zhang, Q.S. Comparison of two algorithms for isotropic elastic P and S vector decomposition. Geophysics 2015, 80, T147–T160. [Google Scholar] [CrossRef]
- He, B.S.; Zhang, H.X. Vector prestack depth migration of multicomponent wavefield. Oil Geophys. Prospect. 2006, 41, 369–374. [Google Scholar]
- Li, Z.C.; Yong, P.; Huang, J.P. Elastic wave reverse time migration based on vector wavefield seperation. J. China Univ. Pet. (Ed. Nat. Sci.) 2016, 40, 42–48. [Google Scholar]
- Vidale, J.E. Complex polarization analysis of particle motion. Bull. Seismol. Soc. Am. 1986, 76, 1393–1405. [Google Scholar]
- Crampin, S.; Lovell, J.H. A decade of shear-wave splitting in the Earth’s crust: What does it mean? What use can we make of it? And what should we do next? Geophys. J. R. Astron. Soc. 1991, 107, 387–407. [Google Scholar] [CrossRef]
- Lilly, J.M.; Park, J. Multiwavelet spectral and polarization analyses of seismic records. Geophys. J. Int. 1995, 122, 1001–1021. [Google Scholar] [CrossRef]
- Lu, J.; Wang, Y.; Yang, C.Y. Instantaneous polarization filtering focused on suppression of surface waves. Appl. Geophys. 2010, 7, 88–97. [Google Scholar] [CrossRef]
- Reading, A.M.; Mao, W.; Gubbins, D. Polarization filtering for automatic picking of seismic data and improved converted phase detection. Geophys. J. Int. 2001, 147, 227–234. [Google Scholar] [CrossRef]
- Diallo, M.S.; Kulesh, M.; Holschneider, M.; Scherbaum, F.; Adler, F. Characterization of polarization attributes of seismic waves using continuous wavelet transforms. Geophysics 2006, 71, V67–V77. [Google Scholar] [CrossRef]
- Wang, C.; Wang, Y. Ground roll attenuation using polarization analysis in the t-f-k domain. Geophys. J. Int. 2017, 210, 240–254. [Google Scholar] [CrossRef]
- Wang, C.; Wang, Y.; Wang, X.K.; Xun, C. Multicomponent seismic noise attenuation with multivariate order statistic filters. J. Appl. Geophys. 2016, 133, 70–81. [Google Scholar] [CrossRef]
- Xun, C.; Wang, C.; Wang, Y. The application of multi-directional vector median filtering in multi-component seismic data. Geophys. Prospect. Pet. 2016, 55, 703–710. [Google Scholar]
- Rodriguez, I.V.; Bonar, D.; Sacchi, M. Microseismic data denoising using a 3C group sparsity constrained time-frequency transform. Geophysics 2012, 77, V21–V29. [Google Scholar] [CrossRef]
- Lei, J. A method for non-orthogonal seismic polarization-vector separation. Geophys. J. Int. 2005, 162, 965–974. [Google Scholar] [CrossRef]
- Lu, J.; Wang, Y.; Yao, C. Separating P- and S-waves in an affine coordinate system. J. Geophys. Eng. 2012, 9, 12–18. [Google Scholar] [CrossRef]
- Li, Z.Y. Separation of P-and S-Waves in Elastic Seismic Wavefield; University of Chinese Academy of Sciences: Beijing, China, 2013. [Google Scholar]
- Shimshoni, M.; Smith, S.W. Seismic signal enhancement with three-component detectors. Geophysics 1964, 29, 664–671. [Google Scholar] [CrossRef]
- White, J.E. Motion product seismograms. Geophysics 1964, 29, 288–298. [Google Scholar] [CrossRef]
- Chen, Y.; Gao, L.; Zhang, F.F. A method to enhance the signal/noise ratio of three component seismic data base on the polarization analysis in frequency domain. Prog. Geophys. 2007, 22, 255–261. [Google Scholar]
- Du, Z.; Foulger, G.R.; Mao, W. Noise reduction for broad-band, three-component seismograms using data-adaptive polarization filters. Geophys. J. Int. 2000, 141, 820–828. [Google Scholar] [CrossRef]
- Flinn, E.A. Signal analysis using rectilinearity and direction of particle motion. IEEE Proc. 1965, 12, 1874–1876. [Google Scholar] [CrossRef]
- Jurkevics, A. Polarisation analyis of three-component array data. Bull. Seismol. Soc. Am. 1988, 78, 1725–1743. [Google Scholar]
- Chen, H.F.; Li, X.Y.; Qian, Z.P.; Zhao, G.L. Robust adaptive polarization analysis method for eliminating ground roll in 3C land seismics. Appl. Geophys. 2013, 10, 295–304. [Google Scholar] [CrossRef]
- Diallo, M.; Kulesh, M.; Holschneider, M. Instantaneous Polarization Attributes Based on Adaptive Covariance Method. Geophysics 2006, 71, V99. [Google Scholar] [CrossRef]
- Ma, J.Q. Research on Adaptive Polarization Filtering for Multi-Component Seismic Data; Chang’an University: Chang’an, China, 2012. [Google Scholar]
- René, R.M.; Fitter, J.L.; Forsyth, P.M.; Kim, K.Y.; Murray, D.J.; Walters, J.K.; Westerman, J.D. Multicomponent seismic studies using complex trace analysis. Geophysics 1986, 51, 1235–1251. [Google Scholar] [CrossRef]
- Morozov, I.B.; Smithson, S.B. Instantaneous polarization attributes and directional fitering. Geophysics 1996, 61, 872–881. [Google Scholar] [CrossRef]
- Schimmel, M.; Gallart, J. The use of instantaneous polarization attributes for seismic signal detection and image enhancement. Geophys. J. Int. 2003, 155, 653–668. [Google Scholar] [CrossRef]
- Park, J.; Vernon, F.L.; Lindberg, C.R. Frequency Dependent Polarization Analysis of High-Frequency Seisrnograms. J. Geophys. Res. Solid Earth 1987, 92, 12664–12674. [Google Scholar] [CrossRef]
- Kulesh, M.; Diallo, M.S.; Holschneider, M. Polarization analysis in the wavelet domain based on the adaptive covariance method. Geophys. J. Int. 2007, 170, 667–678. [Google Scholar] [CrossRef]
- D’Auria, L.; Giudicepietro, F.; Martini, M. Polarization Analysis in the Discrete Wavelet Domain: An Application to Volcano Seismology. Bull. Seismol. Soc. Am. 2010, 100, 670–683. [Google Scholar] [CrossRef]
- Pinnegar, C.R. Polarization analysis and polarization filtering of three-component signals with the time frequency S transform. Geophys. J. Int. 2006, 165, 596–606. [Google Scholar] [CrossRef]
- Tan, Y.Y.; He, C.; Wang, Y.D.; Zhao, Z. Ground roll attenuation using a time-frequency dependent polarization filter based on the S transform. Appl. Geophys. 2013, 10, 279–294. [Google Scholar] [CrossRef]
- Galiana-Merino, J.J.; Parolai, S.; Rosa-Herranz, J. Seismic wave characterization using complex trace analysis in the stationary wavelet packet domain. Soil Dyn. Earthq. Eng. 2011, 31, 1565–1578. [Google Scholar] [CrossRef]
- Nikolaidis, N.; Pitas, I. Multichannel L filters based on reduced ordering. IEEE Trans. Circuits Syst. Video Technol. 1996, 6, 470–482. [Google Scholar] [CrossRef]
- Pitas, I.; Tsakalides, P. Multivariate Ordering in Color Image Filtering. IEEE Trans. Circuits Syst. Video Technol. 1991, 1, 247–259. [Google Scholar] [CrossRef]
- Lucat, L.; Siohan, P. Vector-median type filters and fast-computation algorithms. In Proceedings of the ISCAS ’97—IEEE International Symposium on Circuits and Systems, Hong Kong, China, 9–12 June 1997; Volumes I–IV, pp. 2469–2472. [Google Scholar]
- Xu, J.T.; Wang, L.; Shi, Z.F. A switching weighted vector median filter based on edge detection. Signal Process. 2014, 98, 359–369. [Google Scholar] [CrossRef]
- Trahanias, P.E.; Karakos, D.; Venetsanopoulos, A.N. Directional processing of color images: Theory and experimental results. IEEE Trans. Image Process. 1996, 5, 868–880. [Google Scholar] [CrossRef]
- Pitas, I.; Venetsanopoulos, A.N. Order-Statistics in Digital Image-Processing. Proc. IEEE 1992, 80, 1893–1921. [Google Scholar] [CrossRef]
- Huo, S.D.; Luo, Y.; Kelamis, P.G. Simultaneous sources separation via multidirectional vector-median filtering. Geophysics 2012, 77, V123–V131. [Google Scholar] [CrossRef]
- Liu, Y.K. Noise reduction by vector median filtering. Geophysics 2013, 78, V79–V86. [Google Scholar] [CrossRef]
- Aharon, M. Overcomplete Dictionaries for Sparse Representation of Signals; Technion—Israel Institute of Technology: Haifa, Israel, 2006. [Google Scholar]
- Aharon, M.; Elad, M.; Bruckstein, A. K-SVD: An algorithm for designing overcomplete dictionaries for sparse representation. IEEE Trans. Signal Process. 2006, 54, 4311–4322. [Google Scholar] [CrossRef]
- Mallat, S.G.; Zhang, Z.F. Matching Pursuits with Time-Frequency Dictionaries. IEEE Trans. Signal Process. 1993, 41, 3397–3415. [Google Scholar] [CrossRef]
- Tropp, J.A. Greed is good: Algorithmic results for sparse approximation. IEEE Trans. Inf. Theory 2004, 50, 2231–2242. [Google Scholar] [CrossRef]
- Chen, S.S.B.; Donoho, D.L.; Saunders, M.A. Atomic decomposition by basis pursuit. Siam Rev. 2001, 43, 129–159. [Google Scholar] [CrossRef]
- Li, H.S.; Wu, G.C.; Yin, X.Y. Morphological component analysis in seismic data reconstrution. Oil Geophys. Prospect. 2012, 47, 236–243. [Google Scholar]
- Chen, W.C.; Wang, W.; Gao, J.H. Sparsity optimized separation of Ground-roll noise based on morphological diversity of seismic waveform components. Chin. J. Geophys. 2013, 56, 2771–2782. [Google Scholar]
- Xu, X.H.; Qu, G.Z.; Zhang, Y.; Bi, Y.Y.; Wang, J.J. Ground-roll separation of seismic data based on morphological component analysis in two-dimensional domain. Appl. Geophys. 2016, 13, 116–126. [Google Scholar] [CrossRef]
- Liang, D.H.; Chen, S.C. Deconvolution of seismic data based on L0 norm sparse constrain. Geophys. Prospect. Pet. 2014, 53, 397–403. [Google Scholar]
- Yuan, M.; Lin, Y. Model selection and estimation in regression with grouped variables. J. R. Stat. Soc. Ser. B Stat. Methodol. 2006, 68, 49–67. [Google Scholar] [CrossRef]
- Fornasier, M.; Rauhut, H. Recovery algorithms for vector-valued data with joint sparsity constraints. Siam J. Numer. Anal. 2008, 46, 577–613. [Google Scholar] [CrossRef]
- Eldar, Y.C.; Bolcskei, H. Block-sparsity: Coherence and efficient recovery. In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, Taipei, Taiwan, 19–24 April 2009; pp. 2885–2888. [Google Scholar]
- Beck, A.; Teboulle, M. A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems. Siam J. Imaging Sci. 2009, 2, 183–202. [Google Scholar] [CrossRef]
- Jiang, X.X.; Lin, J.; Ye, F.; Zheng, F. Separation of P-P and P-SV wavefields by high resolution parabolic Radon transform. J. Appl. Geophys. 2015, 119, 192–201. [Google Scholar] [CrossRef]
- Hu, T.Y.; Zhang, G.J.; Zhao, W.; Wen, S.L. Decompostion of multicomponent seismic wavefields. Chin. J. Geophys. 2004, 47, 504–508. [Google Scholar] [CrossRef]
- Yao, D.Z.; Zhou, X.X.; Zhong, B.S. Method for separating out P-wave or S-wave in VSP data, and its application. Oil Geophys. Prospect. 1993, 28, 623–628. [Google Scholar]
- Sun, R.; McMechan, G.A.; Hsiao, H.H.; Chow, J. Separating P- and S-waves in prestack 3D elastic seismograms using divergence and curl. Geophysics 2004, 69, 286–297. [Google Scholar] [CrossRef]
- Yan, J.; Sava, P. Elastic wavefield separation for VTI media. In Proceedings of the 78th Annual International Meeting, Columbus, OH, USA, 24–29 October 2008; pp. 2191–2195. [Google Scholar]
- Li, Z.Y.; Gu, B.L.; Ma, X.N.; Liang, G.H. Separating P- and S-waves in prestack elastic seismograms using the equivalent form of elastic wave equation. J. Appl. Geophys. 2015, 114, 210–223. [Google Scholar] [CrossRef]
- Ma, D.T.; Zhu, G.M. Numerical modeling of P-wave and S-wave separation in elastic wavefield. Oil Geophys. Prospect. 2003, 38, 482–486. [Google Scholar]
- Li, X.Y.; MacBeth, C.; Crampin, S. Interpreting non-orthogonal split shear waves for seismic anisotropy in multicomponent VSPS. Geophys. Prospect. 1998, 46, 1–27. [Google Scholar] [CrossRef]
- Song, Z.C.; Lei, J. Analyzing and correcting the scatter in measurement of time-delays between fast ans slow shear-waves with near-field earthquakes. Chin. Sci. Bull. 2017, 62, 3356–3368. [Google Scholar] [CrossRef]
- Hitzer, E.; Sangwine, S.J. Quaternion and Clifford Fourier Transforms and Wavelets; Birkhäuser: Basel, Switzerland, 2015. [Google Scholar]
- De Lathauwer, L. Signal Processing Based on Multilinear Algebra. Ph.D. Thesis, Katholieke Universiteit, Leuven, Belgium, 1997. [Google Scholar]
- Esch, J. Geometric Algebra for Electrical and Electronic Engineers. Proc. IEEE 2014, 102, 1338–1339. [Google Scholar] [CrossRef]
- Paulus, C.; Mars, J.; Gounon, P. Wideband spectral matrix filtering for multicomponent sensors array. Signal Process. 2005, 85, 1723–1743. [Google Scholar] [CrossRef]
- Chan, W.L.; Choi, H.; Baraniuk, R.G. Coherent multiscale image processing using dual-tree quaternion wavelets. IEEE Trans. Image Process. 2008, 17, 1069–1082. [Google Scholar] [CrossRef]
- Jia, X.N. Quaternion Bispectrum and Its Application in Color Image Processiong; Jilin University: Changchun, China, 2014. [Google Scholar]
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Wang, C.; Wang, Y.; Sun, P.; Li, Y. Discussions on the Processing of the Multi-Component Seismic Vector Field. Appl. Sci. 2019, 9, 1770. https://doi.org/10.3390/app9091770
Wang C, Wang Y, Sun P, Li Y. Discussions on the Processing of the Multi-Component Seismic Vector Field. Applied Sciences. 2019; 9(9):1770. https://doi.org/10.3390/app9091770
Chicago/Turabian StyleWang, Chao, Yun Wang, Pengyuan Sun, and Yuanfang Li. 2019. "Discussions on the Processing of the Multi-Component Seismic Vector Field" Applied Sciences 9, no. 9: 1770. https://doi.org/10.3390/app9091770