Deblending of Simultaneous-source Seismic Data using Fast Iterative Shrinkage-thresholding Algorithm with Firm-thresholding

• Autorzy: Qu S. , Zhou H. , Liu R. , Chen Y. , Zu S. , Yu S. , Yuan J. , Yang Y.

Identyfikatory

DOI

10.1515/acgeo-2016-0045

• Języki publikacji: EN

Abstrakty

EN

In this paper, an improved algorithm is proposed to separate blended seismic data. We formulate the deblending problem as a regularization problem in both common receiver domain and frequency domain. It is suitable for different kinds of coding methods such as random time delay discussed in this paper. Two basic approximation frames, which are iterative shrinkage-thresholding algorithm (ISTA) and fast iterative shrinkage-thresholding algorithm (FISTA), are compared. We also derive the Lipschitz constant used in approximation frames. In order to achieve a faster convergence and higher accuracy, we propose to use firm-thresholding function as the thresholding function in ISTA and FISTA. Two synthetic blended examples demonstrate that the performances of four kinds of algorithms (ISTA with soft- and firm-thresholding, FISTA with soft- and firm-thresholding) are all effective, and furthermore FISTA with a firm-thresholding operator exhibits the most robust behavior. Finally, we show one numerically blended field data example processed by FISTA with firm-thresholding function.

Słowa kluczowe

EN

regularization; simultaneous-source; firm-thresholding; deblending

PL

regularyzacja

• Wydawca: Instytut Geofizyki PAN ; Springer
• Czasopismo: Acta Geophysica
• Rocznik: 2016
• Tom: Vol. 64, no. 4
• Strony: 1064--1092
• Opis fizyczny: Bibliogr. 22 poz.

Twórcy

autor

Qu S.

• State Key Laboratory of Petroleum Resources and Prospecting, Key Lab of Geophysical Exploration of CNPC, Dept. of Geophysics, China University of Petroleum, Beijing, China

autor

Zhou H.

• State Key Laboratory of Petroleum Resources and Prospecting, Key Lab of Geophysical Exploration of CNPC, Dept. of Geophysics, China University of Petroleum, Beijing, China

autor

Liu R.

• Dagang Geophysical Prospecting Branch of BGP, CNPC, Tianjin, China

autor

Chen Y.

• The University of Texas at Austin, Austin, USA

autor

Zu S.

• State Key Laboratory of Petroleum Resources and Prospecting, Key Lab of Geophysical Exploration of CNPC, Dept. of Geophysics, China University of Petroleum, Beijing, China

autor

Yu S.

• State Key Laboratory of Petroleum Resources and Prospecting, Key Lab of Geophysical Exploration of CNPC, Dept. of Geophysics, China University of Petroleum, Beijing, China

autor

Yuan J.

• State Key Laboratory of Petroleum Resources and Prospecting, Key Lab of Geophysical Exploration of CNPC, Dept. of Geophysics, China University of Petroleum, Beijing, China

autor

Yang Y.

• State Key Laboratory of Petroleum Resources and Prospecting, Key Lab of Geophysical Exploration of CNPC, Dept. of Geophysics, China University of Petroleum, Beijing, China

Bibliografia

• Abma, R.L., T. Manning, M. Tanis, J. Yu, and M. Foster (2010), High quality separation of simultaneous sources by sparse inversion. In: Proc. 72nd EAGE Conference and Exhibition incorporating SPE EUROPEC 2010, DOI: 10.3997/2214-4609.201400611.
• Akerberg, P., G. Hampson, J. Rickett, H. Martin, and J. Cole (2008), Simultaneous source separation by sparse radon transform. In: Proc. SEG Annual Meeting, 9-14 November 2008, Las Vegas, USA, SEG-2008-2801, Society of Exploration Geophysicists.
• Beasley, C.J. (2008), A new look at marine simultaneous sources, The Leading Edge 27, 7, 914-917, DOI: 10.1190/1.2954033.
• Beck, A., and M. Teboulle (2009), A fast iterative shrinkage-thresholding algorithm for linear inverse problems, SIAM J. Imaging Sci. 2, 1, 183-202, DOI: 10.1137/080716542.
• Bruce, A.G., and H.-Y. Gao (1996), Understanding waveshrink: variance and bias estimation, Biometrika 83, 4, 727-745, DOI: 10.1093/biomet/83.4.727.
• Candes, E.J., and L. Demanet (2005), The curvelet representation of wave propagators is optimally sparse, Commun. Pure Appl. Math. 58, 11, 1472-1528, DOI: 10.1002/cpa.20078.
• Candes, E.J., and T. Tao (2005), Decoding by linear programming, IEEE Trans. Inf. Theory 51, 12, 4203-4215, DOI: 10.1109/TIT.2005.858979.
• Chambolle, A. (2004), An algorithm for total variation minimization and applications, J. Math. Imaging Vis. 20, 1-2, 89-97, DOI: 10.1023/B:JMIV. 0000011325.36760.1e.
• Chartrand, R. (2007), Exact reconstruction of sparse signals via nonconvex minimization, IEEE Signal Process. Lett. 14, 10, 707-710, DOI: 10.1109/LSP. 2007.898300.
• Chen, Y., and J. Ma (2014), Random noise attenuation by f-x empirical-mode decomposition predictive filtering, Geophysics 79, 3, V81-V91, DOI: 10.1190/geo2013-0080.1.
• Chen, Y., S. Fomel, and J. Hu (2014a), Iterative deblending of simultaneous-source seismic data using seislet-domain shaping regularization, Geophysics 79, 5, V179-V189, DOI: 10.1190/geo2013-0449.1.
• Chen, Y., J. Yuan, Z. Jin, K. Chen, and L. Zhang (2014b), Deblending using normal moveout and median filtering in common-midpoint gathers, J. Geophys. Eng. 11, 4, 045012, DOI: 10.1088/1742-2132/11/4/045012.
• Daubechies, I., M. Defrise, and C. De Mol (2004), An iterative thresholding algorithm for linear inverse problems with a sparsity constraint, Commun. Pure Appl. Math. 57, 11, 1413-1457, DOI: 10.1002/cpa.20042.
• Donoho, D.L. (2006), For most large underdetermined systems of linear equations the minimal 1-norm solution is also the sparsest solution, Commun. Pure Appl. Math. 59, 6, 797-829, DOI: 10.1002/cpa.20132.
• Doulgeris, P., K. Bube, G. Hampson, and G. Blacquiere (2012), Convergence analysis of a coherency-constrained inversion for the separation of blended data, Geophys. Prospect. 60, 4, 769-781, DOI: 10.1111/j.1365-2478.2012.
• 01088.x.
• Figueiredo, M.A., and R.D. Nowak (2003), An EM algorithm for wavelet-based image restoration, IEEE Trans. Image Process. 12, 8, 906-916, DOI: 10.1109/ TIP.2003.814255.
• Gao, H.-Y., and A.G. Bruce (1997), Waveshrink with firm shrinkage, Statistica Sinica 7, 4, 855-874.
• Huo, S., Y. Luo, and P. Kelamis (2009), Simultaneous sources separation via multidirectional vector-median filter. In: Proc. SEG Annual Meeting, 25-30 October 2009, Houston, USA, SEG-2009-0031, Society of Exploration Geophysicists.
• Lin, T.T.Y., and F.J. Herrmann (2009), Designing simultaneous acquisitions with compressive sensing. In: Proc. 71st EAGE Conference and Exhibition incorporating SPE EUROPEC 2009, DOI: 10.3997/2214-4609.201400276.
• Mahdad, A., P. Doulgeris, and G. Blacquiere (2011), Separation of blended data by iterative estimation and subtraction of blending interference noise, Geophysics 76, 3, Q9-Q17, DOI: 10.1190/1.3556597.
• Mahdad, A., P. Doulgeris, and G. Blacquiere (2012), Iterative method for the separation of blended seismic data: discussion on the algorithmic aspects, Geophys. Prospect. 60, 4, 782-801, DOI: 10.1111/j.1365-2478.2012. 01084.x.
• Qu, S., H. Zhou, H. Chen, S. Zu, and L. Zhi (2014), Separation of simultaneous vibroseis data. In: Proc. SEG Annual Meeting, 26-31 October 2014, Denver, USA, SEG-2014-0182, Society of Exploration Geophysicists.