Seismic absorption compensation is an important processing approach to mitigate the attenuation effects caused by intrinsic inelasticity of subsurface media and to enhance the seismic resolution. However, conventional absorption compensation approaches ignore the spatial connection along seismic traces, which makes the compensation result vulnerable to high frequency noise amplification, thus reducing the signal to noise ratio (SNR) of the result. To alleviate this issue, we have developed a structurally constrained multichannel absorption compensation (SC-MAC) algorithm. In the cost function of this algorithm, we exploit a L1 norm to constrain the reflectivity series and a L2 norm to regularize the reflection structural characteristic of the compensation data. The reflection structural characteristic operator (RSC-operator), extracted from the observed seismic data, is the core of the structural regularization. We then solve the cost function of SC-MAC by the alternating direction method of multipliers (ADMM). Benefiting from the introduction of reflection structure constraint, the SC-MAC improves the stability of compensation result and inhibits the amplification of high frequency noise. Synthetic and real data examples demonstrate that the proposed method is more robust to random noise and can not only improve the resolution of seismic data, but also maintain the SNR of the compensation result.


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  1. Abma, R. and Claerbout, J.
    [1995] Lateral prediction for noise attenuation by t-x and f-x techniques. Geophysics, 60(6), 1887–1896.
    [Google Scholar]
  2. Claerbout, J.
    [1988] Multidimensional recursive filters via a helix. Geophysics, 63(5), 1532–1541.
    [Google Scholar]
  3. Du, X., Li, G., Zhang, M., Li, H., Yang, W. and Wang, W.
    [2018] Multichannel band-controlled decon-volution based on a data-driven structural regularization. Geophysics, 83(5), R401–R411.
    [Google Scholar]
  4. Gholami, A.
    [2016] A fast automatic multichannel blind seismic inversion for high-resolution impedance recovery. Geophysics, 81(5), V357–V364.
    [Google Scholar]
  5. Hamid, H. and Pidlisecky, A.
    [2015] Multitrace impedance inversion with lateral constraints. Geophysics, 80(6), M101–M111.
    [Google Scholar]
  6. Margrave, G.F.
    [1998] Theory of nonstationary linear filtering in the Fourier domain with application to time-variant filtering. Geophysics, 63(1), 244–259.
    [Google Scholar]
  7. Oliveira, S.A.M. and Lupinacci, W.M.
    [2013] L1 norm inversion method for deconvolution in attenuating media. Geophysical Prospecting, 61(4), 771–777.
    [Google Scholar]
  8. Wang, S. and Chen, X.
    [2014] Absorption-compensation method by L1-norm regularization. Geophysics, 79(3), V107–V114.
    [Google Scholar]
  9. Wang, Y.
    [2002] A stable and efficient approach of inverse Q filtering. Geophysics, 67(2), 657–663.
    [Google Scholar]
  10. [2006] Inverse Q-filter for seismic resolution enhancement. Geophysics, 71(3), V51–V60.
    [Google Scholar]
  11. Zhang, C. and Ulrych, T.J.
    [2007] Seismic absorption compensation: A least squares inverse scheme. Geophysics, 72(6), R109–R114.
    [Google Scholar]

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