• DocumentCode
    3427233
  • Title

    Research on the high-efficiency ARMA model applied in seismic wavelet estimation

  • Author

    Sun Hong-Tao ; Dai Yong-shou ; Wang Shao-shui ; Peng Xing

  • Author_Institution
    Coll. of Inf. & Control Eng., China Univ. of Pet., Dongying, China
  • fYear
    2010
  • fDate
    24-28 Oct. 2010
  • Firstpage
    164
  • Lastpage
    167
  • Abstract
    On the assumption that the seismic wavelet is causal and nonminimum phase, an ARMA model is introduced to fit the seismic trace. The SVD method based on autocorrelation is used to determine AR order; and the author proposes a new MA model order determination method via combining the information theoretic criteria method with the method based on higher-order cumulant in order to improve the accuracy of MA order determination. The autocorrelation-based SVD-TLS method and cumulant-based method are used to obtain AR parameters and MA parameters respectively. Theoretical analysis and numerical simulations demonstrate the feasibility of the wavelet extraction approach.
  • Keywords
    autoregressive moving average processes; correlation methods; higher order statistics; singular value decomposition; wavelet transforms; AR parameter; MA model order determination method; SVD method; autocorrelation based SVD-TLS method; high efficiency ARMA model; higher order cumulant method; information theoretic criteria method; numerical simulation; seismic trace; seismic wavelet estimation; wavelet extraction; Accuracy; Autoregressive processes; Correlation; Estimation; Mathematical model; Noise; Parameter estimation; ARMA model; order determination; seismic wavelet;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing (ICSP), 2010 IEEE 10th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-5897-4
  • Type

    conf

  • DOI
    10.1109/ICOSP.2010.5657125
  • Filename
    5657125