1887
Volume 49, Issue 6
  • ISSN: 0812-3985
  • E-ISSN: 1834-7533

Abstract

[

Building on the concepts of cohesion degree and local relaxation, we propose an integrated hierarchical equilibrium parallel finite-element reverse time migration (HEP-FE-RTM) algorithm, which is a fine-grained central processing unit (CPU) parallel computation method in two-level host-sub-processors mode. A single master process is responsible for data reading and controlling the progress of the calculation, while each subordinate process deals with a part of the depth domain space. This algorithm is able to achieve single source forward-modelling and inversion calculation using more than 2000 CPUs. On the premise of controlling iteration times for convergence, sub-module/processors only communicate with their adjacent counterparts and the host processor, so the level of data exchange is proportional to cohesion degree. This HEP-FE-RTM algorithm has the distinct advantage that parallel efficiency does not decrease as the number of processors increases. In two-level host-sub-processors mode, more than 2000 processors are used and one billion unknowns are solved. By combining the finite-element implicit dynamic Newmark integral scheme, this approach achieves a prestack reverse time migration (RTM) with high expansion. Making full use of the characteristics of high accuracy and strong boundary adaptability of the finite-element method, through the optimisation of finite-element solving, the HEP-FE-RTM algorithm improved the efficiency of parallel computing and achieved RTM implementation using finite element. Model tests show that this method has a significant effect on both imaging efficiency and accuracy.

,

Building on the concepts of cohesion degree and local relaxation, we propose an integrated hierarchical equilibrium parallel finite-element reverse time migration (HEP-FE-RTM) algorithm, which has the distinct advantage in that parallel efficiency does not decrease as the number of processors increases.

]
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2018-11-01
2026-01-15

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References

  1. Baysal E. Kosloff D. D. Sherwood J. W. C. 1983 Reverse time migration:Geophysics481514152410.1190/1.1441434
     https://doi.org/10.1190/1.1441434 [Google Scholar]
  2. Berenger J.-P. 1994 A perfectly matched layer for the absorption of electromagnetic wave:Journal of Computational Physics11418520010.1006/jcph.1994.1159
     https://doi.org/10.1006/jcph.1994.1159 [Google Scholar]
  3. Cerjan C. Kosloff D. Kosloff R. Reshef M. 1985 A non-reflecting boundary condition for discrete acoustic-wave and elastic-wave equation (shot note):Geophysics5070570810.1190/1.1441945
     https://doi.org/10.1190/1.1441945 [Google Scholar]
  4. Clapp, R. G., 2009, Reverse time migration with random boundaries: 79th Annual International Meeting, SEG, Expanded Abstracts, 2809–2813.
  5. Du Q.-Z. Qin T. 2009 Multicomponent prestack reverse-time migration of elastic waves in transverse isotropic medium:Chinese Journal of Geophysics5247147810.1002/cjg2.1367
     https://doi.org/10.1002/cjg2.1367 [Google Scholar]
  6. Fang Q. 1992 Studies on the accuracy of finite element analysis of implicit Newmark method for wave propagation problems:Explosions and Shock Waves124553
    [Google Scholar]
  7. He B. Zhang H. Han Y. 2010 Reverse-time depth migration of two way acoustic equations and its parallel algorithm:Journal of China Coal Society35458462
    [Google Scholar]
  8. Hemon C. 1978 Equations d’onde et modeles:Geophysical Prospecting2679082110.1111/j.1365‑2478.1978.tb01634.x
     https://doi.org/10.1111/j.1365-2478.1978.tb01634.x [Google Scholar]
  9. Hu L.-Z. McMechan G. A. 1986 Extrapolation in 2-D variable velocity media:Geophysical Prospecting3470473410.1111/j.1365‑2478.1986.tb00489.x
     https://doi.org/10.1111/j.1365-2478.1986.tb00489.x [Google Scholar]
  10. Liu H. Li B. Liu H. Tong X. L. Liu Q. 2010 The algorithm of high order finite difference pre-stack reverse time migration and GPU implementation:Chinese Journal of Geophysics5360061010.1002/cjg2.1530
     https://doi.org/10.1002/cjg2.1530 [Google Scholar]
  11. Mao F. M. Chen A. D. Yan Y. F. Ye S. D. Liu Q. D. Chen L. Q. Tan Y 2006 Hydrocarbon pooling features and seismic recognizing technologies of small complex fault blocks in Subei basin:Oil & Gas Geology27827839
    [Google Scholar]
  12. Mora P. 1989 Inversion = migration + tomography:Geophysics541575158610.1190/1.1442625
     https://doi.org/10.1190/1.1442625 [Google Scholar]
  13. Symes W. M. 2007 Reverse time migration with optimal checkpointing:Geophysics72SM213SM22110.1190/1.2742686
     https://doi.org/10.1190/1.2742686 [Google Scholar]
  14. Whitmore N. D. Lines L. R. 1986 Vertical seismic profiling depth migration of a salt dome flank:Geophysics511087110910.1190/1.1442164
     https://doi.org/10.1190/1.1442164 [Google Scholar]
  15. Zhang H. Ning S. 2002 Pre-stack reverse time migration of elastic wave equations:Journal of China University of Mining & Technology31371375
    [Google Scholar]
/content/journals/10.1071/EG17128
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A high expansion implicit finite-element prestack reverse time migration method
Exploration Geophysics 49, 844 (2018); https://doi.org/10.1071/EG17128
/content/journals/10.1071/EG17128
/content/journals/10.1071/EG17128
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  • Article Type: Research Article
Keyword(s): cohesion degree; finite element; local relaxation; multi-level parallel; reverse time migration

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