GPU Acceleration Algorithm of the Reverse Time Migration with Seismic Data
DOI:
CSTR:
Author:
Affiliation:

Clc Number:

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Currently,prestack reverse-time migration is the most accurate imaging method for seismic data in seismic prospecting domain. It extrapolating the wave field with the two-way acoustic wave equation, and it can image complex geological structure accurately. The cross-correlation imaging condition is used for the imaging of source wavefield and receiver wavefield at the same time in the paper. For computationally intensive problems of RTM,we introduce the graphics processing unit (GPU) into RTM algorithm, and exploit the multicore advantages of GPU. In this paper,we use the parallel acceleration algorithm base on the CUDA architecture to replace the serial computation on the traditional CPU and accelerate the process of the wavefield extrapolation and cross-correlation imaging in reverse time migration. The test on complex modeling show that we can achieve imaging result for complex medium with high efficiency and precision by pre-stack reverse time migration algorithm base on GPU acceleration. Under the premise of ensuring the calculation accuracy of the RTM, comparing with the traditional CPU calculation,GPU parallel acceleration algorithm can improve the computational efficiency greatly.

    Reference
    Related
    Cited by
Get Citation

柯璇,石颖,刘诗竹.地震资料逆时偏移中的图形处理器加速算法.计算机系统应用,2013,22(11):115-118

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:April 14,2013
  • Revised:May 14,2013
  • Adopted:
  • Online: November 22,2013
  • Published:
Article QR Code
You are the firstVisitors
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-3
Address:4# South Fourth Street, Zhongguancun,Haidian, Beijing,Postal Code:100190
Phone:010-62661041 Fax: Email:csa (a) iscas.ac.cn
Technical Support:Beijing Qinyun Technology Development Co., Ltd.

Beijing Public Network Security No. 11040202500063