Acoustic wave propagation simulation by reduced order modelling

被引:2
|
作者
Basir, Hadi Mahdavi [1 ]
Javaherian, Abdolrahim [1 ,2 ]
Shomali, Zaher Hossein [2 ,3 ]
Firouz-Abadi, Roohollah Dehghani [4 ]
Gholamy, Shaban Ali [5 ]
机构
[1] Amirkabir Univ Technol, Dept Petr Engn, Tehran 158754413, Iran
[2] Univ Tehran, Inst Geophys, Tehran 141556466, Iran
[3] Uppsala Univ, Dept Earth Sci, S-75236 Uppsala, Sweden
[4] Sharif Univ Technol, Dept Aerosp Engn, Tehran 1136511155, Iran
[5] Natl Iranian Oil Co, Explorat Directorate, Dept Geophys, Tehran 1994814695, Iran
关键词
acoustic wave propagation simulation; finite element method (FEM); reduced order modelling (ROM); seismic modelling; REDUCTION; SYSTEMS; EQUATION;
D O I
10.1071/EG16144
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Wave propagation simulation, as an essential part of many algorithms in seismic exploration, is associated with high computational cost. Reduced order modelling(ROM) is a known technique in many different applications that can reduce the computational cost of simulation by employing an approximation of the model parameters. ROM can be carried out using different algorithms. The method proposed in this work is based on using the most important mode shapes of the model, which can be computed by an efficient numerical method. The numerical accuracy and computational performance of the proposed method were investigated over a simple synthetic velocity model and a portion of the SEG/EAGE velocity model. Different boundary conditions were discussed, and among them the random boundary condition had higher performance for applications like reverse time migration (RTM). The capability of the proposed method for RTM was evaluated and confirmed by the synthetic velocity model of SEG/EAGE. The results showed that the proposed ROM method, compared with the conventional finite element method (FEM), can decrease the computational cost of wave propagation modelling for applications with many simulations like the reverse time migration. Depending on the number of simulations, the proposed method can increase the computational efficiency by several orders of magnitudes.
引用
收藏
页码:386 / 397
页数:12
相关论文
共 50 条
  • [31] Efficient SPH simulation of time-domain acoustic wave propagation
    Zhang, Y. O.
    Zhang, T.
    Ouyang, H.
    Li, T. Y.
    ENGINEERING ANALYSIS WITH BOUNDARY ELEMENTS, 2016, 62 : 112 - 122
  • [32] 2,5-D numerical simulation of acoustic wave propagation
    Narayan, JP
    PURE AND APPLIED GEOPHYSICS, 1998, 151 (01) : 47 - 61
  • [33] Simulation of acoustic wave propagation in a nozzle using a characteristic based algorithm
    Sabry, A.S.
    Serag-Eldin, M.A.
    Mahmoud, H.A.
    Journal of Engineering and Applied Science, 2002, 49 (03): : 547 - 560
  • [34] Coupling the BEM/TBEM and the MFS for the numerical simulation of acoustic wave propagation
    Tadeu, Antonio
    Antonio, Julieta
    Castro, Igor
    ENGINEERING ANALYSIS WITH BOUNDARY ELEMENTS, 2010, 34 (04) : 405 - 416
  • [35] Finite-difference modelling of wave propagation in acoustic tilted TI media
    Zhang, LB
    Rector, JW
    Hoversten, GM
    GEOPHYSICAL PROSPECTING, 2005, 53 (06) : 843 - 852
  • [36] A Reduced Model for Fast and Accurate Simulation of Surface Acoustic Wave Devices
    Hashimoto, Ken-ya
    2013 IEEE INTERNATIONAL ULTRASONICS SYMPOSIUM (IUS), 2013, : 1391 - 1394
  • [37] Wave propagation simulation in normal and infarcted myocardium: Computational and modelling issues
    Maglaveras, N
    Van Capelle, FJL
    De Bakker, JMT
    MEDICAL INFORMATICS, 1998, 23 (02): : 105 - 118
  • [38] Performance enhancements of physical systems by reduced-order modelling and simulation
    Gupta, Ankur
    Manocha, Amit Kumar
    INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL, 2020, 36 (01) : 14 - 23
  • [39] Machine learning and reduced order modelling for the simulation of braided stent deployment
    Bisighini, Beatrice
    Aguirre, Miquel
    Biancolini, Marco Evangelos
    Trovalusci, Federica
    Perrin, David
    Avril, Stephane
    Pierrat, Baptiste
    FRONTIERS IN PHYSIOLOGY, 2023, 14
  • [40] Fast Simulation of Nonlinear Dynamical Systems for Application in Reduced Order Modelling
    Nahvi, S. A.
    Bazaz, M. A.
    Nabi, M.
    Janardhanan, S.
    2014 EUROPEAN CONTROL CONFERENCE (ECC), 2014, : 1092 - 1097