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EMD Method Applied to Identification of Logging Sequence Strata

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Wybrane pełne teksty z tego czasopisma
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this work, we compare Fourier transform, wavelet transform, and empirical mode decomposition (EMD), and point out that EMD method decomposes complex signal into a series of component functions through curves of local mean value. Each of Intrinsic Mode Functions (IMFs - component functions) contains all the information on the original signal. Therefore, it is more suitable for the interface identification of logging sequence strata. Well logging data reflect rich geological information and belong to non-linear and non-stationary signals and EMD method can deal with non-stationary and non-linear signals very well. By selecting sensitive parameters combination that reflects the regional geological structure and lithology, the combined parameter can be decomposed through EMD method to study the correlation and the physical meaning of each intrinsic mode function. Meanwhile, it identifies the stratigraphy and cycle sequence perfectly and provides an effective signal treatment method for sequence interface.
Czasopismo
Rocznik
Strony
1256--1275
Opis fizyczny
Bibliogr. 18 poz., rys., tab., wykr.
Twórcy
autor
  • State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation (CDUT), Chengdu, China
autor
  • Xi’an Technological University, Computer Science and Engineering College, Xi’an, China
Bibliografia
  • [1] Akansu, A.N., W.A. Serdijn, and I.W. Selesnick (2010), Emerging applications of wavelets: A review, Phys. Comm. 3, 1, 1-18, DOI: 10.1016/j.phycom.2009.07.001.
  • [2] Bogle, M.G.V., J.E. Hearst, V.F.R. Jones, and L. Stoilov (1994), Lissajous knots, J. Knot Theor. Ramif. 3, 2, 121-140, DOI: 10.1142/S0218216594000095.
  • [3] Bowman, D.C., and J.M. Lees (2013), The Hilbert-Huang transform: A high resolution spectral method for nonlinear and nonstationary time series, Seismol. Res. Lett. 84, 6, 1074-1080, DOI: 10.1785/0220130025.
  • [4] de Lima, E.R., A.O. Andrade, J.L. Pons, P. Kyberd, and S.J. Nasuto (2006), Empirical mode decomposition: a novel technique for the study of tremor time series, Med. Biol. Eng. Comput. 44, 7, 569-582, DOI: 10.1007/s11517-006-0065-x.
  • [5] Flandrin, P., G. Rilling, and P. Gonçalvés (2004), Empirical mode decomposition as a filter bank, IEEE Signal Process. Lett. 11, 2, 112-114, DOI: 10.1109/ LSP.2003.821662.
  • [6] Hoste, J., and L. Zirbel (2006), Lissajous knots and knots with Lissajous projections, arXiv: math/0605632 [math.GT], 1-17.
  • [7] Huang, N.E., and Z. Wu (2008), A review on Hilbert-Huang transform: Method and its applications to geophysical studies, Rev. Geophys. 46, 2, RG2006, DOI: 10.1029/2007RG000228.
  • [8] Huang, N.E., Z. Shen, S.R. Long, M.C. Wu, H.H. Shih, Q. Zheng, N.C. Yen, C.C. Tung, and H.H. Liu (1998), The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis, Proc. R. Soc. Lond. A. 454, 1971, 903-995, DOI: 10.1098/rspa.1998.0193.
  • [9] Huang, N.E., Z. Shen, and S.R. Long (1999), A new view of nonlinear water waves: the Hilbert spectrum, Ann. Rev. Fluid Mech. 31, 417-457, DOI: 10.1146/ annurev.fluid.31.1.417.
  • [10] Li, Y.-J., X.-Y. Hu, and Z.-X. He (2010), Application situation and prospects of Hilbert- Huang transform in geophysics, Chin. J. Eng. Geophys. 7, 5, 537-543, (in Chinese).
  • [11] Serra, O., and H.T. Abbott (1982), The contribution of logging data to sedimentology and stratigraphy, Soc. Petrol. Eng. J. 22, 1, 117-131, DOI: 10.2118/ 9270-PA.
  • [12] van Wagoner, J.C., R.M. Mitchum, K.M. Campion, and V.D. Rahmanian (1990), Siliciclastic Sequence Stratigraphy in Well Logs, Cores, and Outcrops: Concepts for High-Resolution Correlation of Time and Facies, AAPG Methods in Exploration Series, No. 7, The American Association of Petroleum Geologists, Tulsa, USA.
  • [13] Wawrzyniak, K. (2010), Application of time-frequency transforms to processing of full waveforms from acoustic logs, Acta Geophys. 58, 1, 49-82, DOI: 10.2478/s11600-009-0043-4.
  • [14] Wu, Z., and N.E. Huang (2004), A study of the characteristics of white noise using the empirical mode decomposition method, Proc. R. Soc. Lond. A 460, 2046, 1597-1611, DOI: 10.1098/rspa.2003.1221.
  • [15] Zhang, T., and C.-Y. Nie (2011), Information extraction of acoustic logging for oil layers based on EMD time-frequency analysis, J. Changchun Univ. 21, 8, 15-18 (in Chinese).
  • [16] Zheng, R.-C., S.-M. Yin, and J. Peng (2000), Sedimentary dynamic analysis of sequence structure and stacking pattern of base-level cycle, Acta Sediment.
  • [17] Sin. 18, 3, 369-375 (in Chinese). Zheng, R.-C., J. Peng, and C.-R. Wu (2001), Grade division of base-level cycles of terrigenous basin and its implications, Acta Sediment. Sin. 19, 2, 249-255 (in Chinese).
  • [18] Zheng, T.-X., and L.-H. Yang (2007), Discussion and improvement on empirical mode decomposition algorithm, Acta Scient. Nat. Univ. Sunyatseni 46, 1, 1-6 (in Chinese).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-57b5cde6-097a-47f8-94d8-f746d6151101
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