Abstract
The gradient preconditioning approach based on seismic wave energy can effectively avoid the huge memory consumption of the gradient preconditioning algorithms based on the Hessian matrix. However, the accuracy of this approach is prone to be influenced by the energy of reflected waves. To tackle this problem, the paper proposes a new gradient preconditioning method based on the energy of transmitted waves. The approach scales the gradient through a precondition factor, which is calculated by the ‘approximate transmission wavefield’ simulation based on the nonreflecting acoustic wave equation. The method requires no computing nor storing of the Hessian matrix and its inverse matrix. Furthermore, the proposed method can effectively eliminate the effects of geometric spreading and disproportionality in the gradient illumination. The results of model experiments show that the time-domain full waveform inversion (FWI) using the gradient preconditioning based on transmitted wave energy can achieve higher inversion accuracy for deep high-velocity bodies and their underlying strata in comparison with the one using the gradient preconditioning based on seismic wave energy. The field marine seismic data test shows that our proposed method is also highly applicable to the FWI of field marine seismic data.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Alkhalifah, T., 2015. Scattering angle based filtering of the waveform inversion gradients. Geophysical Journal International, 200: 363–373.
Baysal, E., Kosloff, D. D., and Sherwood, J. W. C., 1984. A two-way nonreflecting wave equation. Geophysics, 49: 132–141.
Brossier, R., Operto, S., and Virieux, J., 2009. Seismic Imaging of complex onshore structures by 2D elastic frequency-domain full-waveform inversion. Geophysics, 74 (6): WCC105–WCC118.
Bunks, C., Fatimetou, M. S., Zaleski, S., and Chavent, G., 1995. Multiscale seismic waveform inversion. Geophysics, 60 (5): 1457–1473.
Choi, Y., Min, D. J., and Shin, C., 2008. Frequency-domain elastic full waveform inversion using the new pseudo-Hessian matrix: Experience of elastic Marmousi-2 synthetic data. Bulletin of the Seismological Society of America, 98 (5): 2402–2415.
Diaz, E., 2011. Fast full waveform inversion with random shot decimation. 81st Annual International Meeting, SEG. San Antonio, 2804–2808.
Etgen, J. T., 1986a. High-order finite-difference reverse time migration with the 2-way non-reflecting wave equation. SEP Report, 48: 133–146.
Etgen, J. T., 1986b. Prestack reverse time migration of shot profiles. SEP Report, 50: 151–169.
Guitton, A., Ayeni, G., and Gonzolez, G., 2010. A preconditioning scheme for full waveform inversion. 80th Annual International Meeting, SEG. Denver, 1008–1012.
Krebs, J. R., Anderson, J. E., David, H., and Ramesh, N., 2009. Fast full-wavefield seismic inversion using encoded sources. Geophysics, 74 (6): WCC177–WCC188.
Mao, J., Wu, R., and Wang, B., 2012. Multiscale full waveform inversion using GPU. 82nd Annual International Meeting, SEG. Houston, 1–7.
Morales, J. L., and Nocedal, J., 2002. Enriched methods for large-scale unconstrained optimization. Computational Optimization and Applications, 21: 143–154.
Plessix, R. E., and Mudler, W. A., 2004. Frequency-domain finite-difference amplitude-preserving migration. Geophysical Journal International, 157: 975–987.
Pratt, G., and Shin, C., 1998. Gauss-Newton and full Newton methods in frequency-space seismic waveform inversion. Geophysical Journal International, 133 (2): 341–362.
Shin, C., Yoon, K. G., and Marfurt, K. J., 2001. Efficiemt calculation of a partial-derivative wavefield using reciprocity for seismic imaging and inversion. Geophysics, 66 (6): 1856–1863.
Song, P., 2013. The time-domain full waveform inversion based on high-performance multi-card GPU computing. PhD thesis. Ocean University of China.
Tarantola, A., 1984. Inversion of seismic reflection data in the acoustic approximation. Geophysics, 49 (8): 1259–1266.
Tarantola, A., 1986. A strategy for nonlinear elastic inversion of seismic reflection data. Geophysics, 51 (10): 1893–1903.
Wang, B., and Gao, J. H., 2011. CUDA-base acceleration of full waveform inversion on GPU. 81st Annual International Meeting, SEG. San Antonio, 2528–2533.
Wang, Y, and Rao, Y., 2009. Reflection seismic waveform tomography. Journal of Geophysical Research, 114 (B3): B03304.
Wang, Y., Dong, L. G., and Liu, Y. Z., 2013. Improved hybrid iterative optimization method for seismic full waveform inversion. Applied Geophysics, 10 (3): 265–277.
Zhang, S. Q., Liu, C. C., Han, L. G., and Yang, X. C., 2013. Frequency multi-scale full waveform inversion based on L-BFGS algorithm simultaneous sources approach. Journal of Jilin University (Earth Science Edition), 43 (3): 1004–1012 (in Chinese with English abstract).
Zhang, Z. G., Huang, L. J., and Lin, Y. Z., 2012a. A wave-energy-based precondition approach to full-waveform inversion in the time domain. 82nd Annual International Meeting, SEG. Houston, 1–5.
Zhang, Z. G., Huang, L. J., and Lin, Y. Z., 2012b. Double-difference elastic-waveform inversion with weighted gradients for monitoring egs reservoirs. 37th Workshop on Geothermal Reservoir Engineering Stanford University. Stanford, SGP-TR-194.
Zhang, Z. G., Lin, Y. Z., and Huang, L. J., 2011. Full-waveform inversion in the time domain with an energy-weighted gradient. 81st Annual International Meeting, SEG. San Antonio, 2772–2776.
Acknowledgements
The authors appreciate the support of the NSFC-Shandong Joint Fund for Marine Science Research Centers (No. U1606401), the National Natural Science Foundation of China (Nos. 41574105 and 41704114), the National Science and Technology Major Project of China (No. 2016ZX05027-002) and Taishan Scholar Project Funding (No. tspd20161007).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Song, P., Tan, J., Liu, Z. et al. Time-Domain Full Waveform Inversion Using the Gradient Preconditioning Based on Transmitted Wave Energy. J. Ocean Univ. China 18, 859–867 (2019). https://doi.org/10.1007/s11802-019-3783-z
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11802-019-3783-z