Abstract：
Multi-source seismic technology is an efficient seismic acquisition method that requires a group of blended seismic data to be separated into single-source seismic data for subsequent processing. The separation of blended seismic data is a linear inverse problem. According to the relationship between the shooting number and the simultaneous source number of the acquisition system, this separation of blended seismic data is divided into an easily determined or overdetermined linear inverse problem and an underdetermined linear inverse problem that is difficult to solve. For the latter, this paper presents an optimization method that imposes the sparsity constraint on wavefields to construct the object function of inversion, and the problem is solved by using the iterative thresholding method. For the most extremely underdetermined separation problem with single-shooting and multiple sources, this paper presents a method of pseudo-deblending with random noise filtering. In this method, approximate common shot gathers are received through the pseudo-deblending process, and the random noises that appear when the approximate common shot gathers are sorted into common receiver gathers are eliminated through filtering methods. The separation methods proposed in this paper are applied to three types of numerical simulation data, including pure data without noise, data with random noise, and data with linear regular noise to obtain satisfactory results. The noise suppression effects of these methods are sufficient, particularly with single-shooting blended seismic data, which verifies the effectiveness of the proposed methods.
WANG Han-Chuang,CHEN Sheng-Chang,ZHANG Bo et al. Separation method for multi-source blended seismic data[J]. APPLIED GEOPHYSICS, 2013, 10(3): 251-264.
[1]
Aaron, P., Borselen, B. R., and Fromyr, E., 2008, Simultaneous Sources: A Controlled Experiment on Different Source Configurations: 79th Ann. Internat. Mtg., Soc. Expl. Geophys., Expanded Abstracts, 56 - 60.
[2]
Akerberg, P., Hampson, G., Rickett, J., et al., 2008, Simultaneous source separation by sparse radon transform: 78th Ann. Internat. Mtg., Soc. Expl. Geophys., Expanded Abstracts, 2801 - 2805.
Beasley, C. J., 2008, A new look at marine simultaneous sources: The Leading Edge, 7(7), 914 - 917.
[5]
Beasley, C. J., Chambers, R. E., and Jiang, Z., 1998, A new look at simultaneous sources: 68th Ann. Internat. Mtg., Soc. Expl. Geophys., Expanded Abstracts, 133 - 135.
[6]
Berkhout, A. J., Blacquière, G., and Verschuur, E., 2008, From simultaneous shooting to blended acquisition: 78th Ann. Internat. Mtg., Soc. Expl. Geophys., Expanded Abstracts, 2831 - 2838.
[7]
Berkhout, A. J., Blacquière, G., and Verschuur, E., 2009, The concept of double blending Combining incoherent shooting with incoherent sensing: 79th Ann. Internat. Mtg., Soc. Expl. Geophys., Expanded Abstracts, 59-62.
[8]
Blacquière, G., Berkhout, A. J., and Verschuur, E., 2009, Survey Design for Blended Acquisition: 79th Ann. Internat. Mtg., Soc. Expl. Geophys., Expanded Abstracts, 56 - 60.
[9]
Candès, E. J., and Donoho, D. L., 2003, New tight frames of curvelets and optimal representations of objects with piecewise C2 singularities: Commun. Pur. Appl. Math., 57(2), 219 - 266.
[10]
Cardoso, J. F., 1998, Blind signal separation: statistical principles: Proceedings of the IEEE, 86(10), 2009 - 2025.
[11]
Daubechies, I., Fornasier, M., and Loris, I., 2008, Accelerated projected gradient method for linear inverse problems with sparsity constraints: J. Fourier Anal. Appl., 14(5 - 6), 764 - 792.
[12]
Demanet, L., and Ying, L., 2007, Curvelets and wave atoms for mirror-extended images: Wavelets XII.
[13]
Gandini, M., Lombardi, F., and Vaccarino, F., 2011, Blind separation of manufacturing variability with independent component analysis: A convolutive approach: Expert Syst. Appl., 38(8), 9939 - 9946.
[14]
Golub, G. H., and Reinsch, C., 1970, Singular value decomposition and least squares solutions: Numer. Math., 14(5), 403 - 420.
[15]
Hampson, G., Stefani, J., Herkenhoff, F., et al., 2008, Acquisition using simultaneous sources: The Leading Edge, 27(7), 918 - 923.
[16]
Huo, S., Luo, Y., and Kelamis, P. G., 2012, Simultaneous sources separation via multi-directional vector-median filter: Geophysics, 77(4), 123 - 131.
[17]
Ikelle, L., 2007, Coding and decoding, seismic data modeling, acquisition and processing: 77th Ann. Internat. Mtg., Soc. Expl. Geophys., Expanded Abstracts, 66 - 70.
[18]
Landweber, L., 1951, An iteration formula for Fredholm integral equations of the first kind: Am. J. Math., 73(3), 615 - 624.
[19]
Lynn, W., Doyle, M., Larner, K., et al., 1987, Experimental investigation of interference from other seismic crews: Geophysics, 52(11), 1501 - 1524.
[20]
Lee, T. W., Lewicki, M. S., Girolami, M., et al., 1999, Blind source separation of more sources than mixtures using overcomplete representations: Signal Processing Letters, IEEE, 6(4), 87 - 90.
[21]
Mahdad, A., Doulgeris, P., and Blacquiere, G., 2010, Separation of blended data by iterative estimation and subtraction of blending interference noises: Geophysics, 76(3), 9 - 17.
[22]
Moerig, R., Barr, F. J., Nyland, D. L., et al., 2002, Simultaneous shooting using cascaded sweeps: 72nd Ann. Internat. Mtg., Soc. Expl. Geophys., Expanded Abstracts, 74 - 76.
[23]
Moore, I., Dragoset, B., Ommundsen, T., et al., 2008, Simultaneous source separation using dithered sources: 78th Ann. Internat. Mtg., Soc. Expl. Geophys., Expanded Abstracts, 2806 - 2810.
[24]
Paige, C. C., and Saunders, M. A., 1981, Towards a generalized singular value decomposition: Siam J. Numer. Anal., 18(3), 398 - 405.
[25]
Spitz, S., Pica, A., and Hampson, G., 2008, Simultaneous source separation: a prediction-subtraction approach: 78th Ann. Internat. Mtg., Soc. Expl. Geophys., Expanded Abstracts, 2811 - 2815.
[26]
Yao, Y., 2002, Geophysical Inversion Basic Theory and Application Method, China University of Geosciences Press, Wuhan, 40 - 50.
2013, Vol. 10 
