Applied Geophysics

, Volume 14, Issue 2, pp 301–313 | Cite as

Improved preconditioned conjugate gradient algorithm and application in 3D inversion of gravity-gradiometry data

  • Tai-Han Wang
  • Da-Nian Huang
  • Guo-Qing Ma
  • Zhao-Hai Meng
  • Ye Li
Article
  • 78 Downloads

Abstract

With the continuous development of full tensor gradiometer (FTG) measurement techniques, three-dimensional (3D) inversion of FTG data is becoming increasingly used in oil and gas exploration. In the fast processing and interpretation of large-scale high-precision data, the use of the graphics processing unit process unit (GPU) and preconditioning methods are very important in the data inversion. In this paper, an improved preconditioned conjugate gradient algorithm is proposed by combining the symmetric successive over-relaxation (SSOR) technique and the incomplete Choleksy decomposition conjugate gradient algorithm (ICCG). Since preparing the preconditioner requires extra time, a parallel implement based on GPU is proposed. The improved method is then applied in the inversion of noisecontaminated synthetic data to prove its adaptability in the inversion of 3D FTG data. Results show that the parallel SSOR-ICCG algorithm based on NVIDIA Tesla C2050 GPU achieves a speedup of approximately 25 times that of a serial program using a 2.0 GHz Central Processing Unit (CPU). Real airborne gravity-gradiometry data from Vinton salt dome (southwest Louisiana, USA) are also considered. Good results are obtained, which verifies the efficiency and feasibility of the proposed parallel method in fast inversion of 3D FTG data.

Keywords

Full Tensor Gravity Gradiometry (FTG) ICCG method conjugate gradient algorithm gravity-gradiometry data inversion CPU and GPU 

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Notes

Acknowledgments

The authors would like to thank Bell Geospace Inc. for providing FTG data from the Vinton salt dome. We also thank the reviewers for their detailed comments and suggestions, which helped to improve the paper.

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Copyright information

© Editorial Office of Applied Geophysics and Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Tai-Han Wang
    • 1
  • Da-Nian Huang
    • 1
  • Guo-Qing Ma
    • 1
  • Zhao-Hai Meng
    • 2
  • Ye Li
    • 3
  1. 1.College of Geo-Exploration Science and TechnologyJilin UniversityChangchunChina
  2. 2.Tianjin Navigation Instrument Research InstituteTianjinChina
  3. 3.Jilin Provincial Electric Power Survey and Design InstituteChangchunChina

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