吉林大学学报(地球科学版) ›› 2018, Vol. 48 ›› Issue (2): 384-393.doi: 10.13278/j.cnki.jjuese.20170262

• 地球物理数据处理与解释技术 • 上一篇    下一篇

基于并行预处理算法的三维重力快速反演

王泰涵1, 黄大年1, 马国庆1, 李野2, 林松1   

  1. 1. 吉林大学地球探测科学与技术学院, 长春 130026;
    2. 吉林省电力勘测设计院, 长春 130021
  • 收稿日期:2017-09-23 出版日期:2018-03-26 发布日期:2018-03-26
  • 通讯作者: 马国庆(1984-),男,副教授,博士,主要从事航空重磁数据采集、数据校正与解释技术方面的研究,E-mail:maguoqing@jlu.edu.cn E-mail:maguoqing@jlu.edu.cn
  • 作者简介:王泰涵(1990-),男,博士研究生,主要从事重力与重力梯度数据处理与解释方法研究,E-mail:thwang15@mails.jlu.edu.cn
  • 基金资助:
    国家重点研发计划项目（2017YFC0602203，2017YFC0601606）；国家油气重大专项（2016ZX05027-002-003）；国家自然科学基金项目（41604098，41404089，41430322）

Three-Dimensional Fast Gravity Inversion Using Parallel Preconditioned Algorithm

Wang Taihan1, Huang Danian1, Ma Guoqing1, Li Ye2, Lin Song1   

  1. 1. College of GeoExploration Science and Technology, Jilin University, Changchun 130026, China;
    2. Jilin Provincial Electric Power Survey and Design Institute, Changchun 130021, China
  • Received:2017-09-23 Online:2018-03-26 Published:2018-03-26
  • Supported by:
    Supported by National Key Research and Development Program of China(2017YFC0602203,2017YFC0601606), National Science and Technology Major Project Task (2016ZX05027-002-03) and National Natural Science Foundation of China (41604098,41404089,41430322)

PDF (PC)

561

摘要： 随着地球物理设备和探测技术的不断发展，快速处理大规模地球物理数据的需求也随之增长。为了解决三维重力数据密度反演的耗时问题，提出一种并行的预处理共轭梯度算法来提高计算效率。本文分别采用两种不同的预处理算子通过组合模型数据反演进行测试比较，并利用迭代残差和计算用时共同评价其加速效果。结果表明：对称逐次超松弛预处理方法比对角预处理方法反演计算速度快，密度结果更贴近实际模型；与传统串行的共轭梯度算法相比，本文并行预处理快速算法可以获得近19倍的加速比。将该算法应用于美国Vinton盐丘的实测重力数据中，反演结果能够很好地圈定出岩体的位置，验证了本文并行预处理共轭梯度法在三维重力数据快速反演中的高效性和可行性。

关键词: 三维重力反演, 预处理共轭梯度算法, 并行算法, 对称逐次超松弛迭代法

Abstract: With the dramatic development of the geophysical equipment and exploration technology, the demand of rapid processing of large-scale geophysical data has been increasing. In order to solve the time-consuming problem of three dimensional gravity data inversion, a parallel implementation of preconditioned conjugate gradient algorithm is proposed to improve the computation efficiency. We adopted and tested two different preconditioned strategies with synthetic data, and evaluated their acceleration quality through observing the residual error of iterations and the running time. The results indicate that the symmetric successive over-relaxation (SSOR) preconditioner has a better performance with density results closer to the true model. Compared with the conventional conjugate gradient algorithm in serial code, our parallel preconditioned conjugated gradient algorithm can result in up to approximately 19x speedup. We used it to the real gravity data from the Vinton salt dome in USA, and the inversion results well delineated the location of the cap-rock, which verified the high efficiency and feasibility of this parallel preconditioned conjugate gradient algorithm in 3D fast gravity inversion.

Key words: 3D gravity inversion, preconditioned conjugate gradient algorithm, parallel algorithm, symmetric successive over-relaxation iteration method

中图分类号: 

  • P631.1
[1] 刘财, 杨宝俊, 冯晅,等. 论油气资源的多元勘探[J]. 吉林大学学报(地球科学版), 2016,46(4):1208-1220. Liu Cai, Yang Baojun, Feng Xuan, et al. Multivariate Exploration Technology of Hydrocarbon Resources[J]. Journal of Jilin University(Earth Science Edition), 2016, 46(4):1208-1220.
[2] Nettleton L L. Gravity and Magnetics in Oil Prospe-cting[M]. New York:McGraw-Hill Companies, 1976.
[3] Hinze W J. The Role of Gravity and Magnetic Methods in Engineering and Environmental Studies[J]. Geotechnical and Environmental Geophysics, 1990, 1:75-126.
[4] Li Y, Oldenburg D W. 3-D Inversion of Magnetic Data[J]. Geophysics, 1996, 61(2):394-408.
[5] Li Y, Oldenburg D W. 3-D Inversion of Gravity Data[J]. Geophysics, 1998, 63(1):109-119.
[6] Bell R E, Anderson R, Pratson L. Gravity Gradio-metry Resurfaces[J]. Leading Edge, 1997, 16(1):55-59.
[7] Lee J B. FALCON Gravity Gradiometer Technology[J]. Exploration Geophysics, 2001, 32(4):247-250.
[8] 黄大年, 于平, 底青云,等. 地球深部探测关键技术装备研发现状及趋势[J]. 吉林大学学报(地球科学版), 2012, 42(5):1485-1496. Huang Danian, Yu Ping, Di Qingyun, et al. Development of Key Instruments and Technologies of Deep Exploration Today and Tomorrow[J]. Journal of Jilin University(Earth Science Edition), 2012,42(5):1485-1496.
[9] Canning F X, Scholl J F. Diagonal Preconditioners for the EFIE Using a Wavelet Basis[J]. IEEE Transactions on Antennas & Propagation, 1996, 44(9):1239-1246.
[10] Pilkington M. 3D Magnetic Imaging Using Conjugate Gradients[J]. Geophysics, 1997, 62(4):1132-1142.
[11] Chen R S, Yung E K N, Chan C H, et al. App-lication of Preconditioned CG-FFT Technique to Method of Lines for Analysis of the Infinite-Plane Metallic Grating[J]. Microwave & Optical Technology Letters, 2000, 24(3):170-175.
[12] Chen R S, Yung K N, Chan C H, et al. Application of the SSOR Preconditioned CG Algorithm to the Vector FEM for 3D Full-Wave Analysis of Electromagnetic-Field Boundary-Value Problems[J]. IEEE Transactions on Microwave Theory & Techniques, 2002, 50(4):1165-1172.
[13] NVIDIA Corporation. NVIDIA CUDA Programming Guide[R]. Santa Clara CA:NVIDIA Corporation, 2008.
[14] Moorkamp M, Jegen M, Roberts A, et al. Massively Parallel Forward Modeling of Scalar and Tensor Gravimetry Data[J]. Computers & Geosciences, 2010, 36(5):680-686.
[15] Chen Z, Meng X, Guo L, et al. GICUDA:A Parallel Program for 3D Correlation Imaging of Large Scale Gravity and Gravity Gradiometry Data on Graphics Processing Units with CUDA[J]. Computers & Geosciences, 2012, 46(3):119-128.
[16] Liu G, Meng X, Chen Z. 3D Magnetic Inversion Based on Probability Tomography and Its GPU Implement[J]. Computers & Geosciences, 2012, 48(9):86-92.
[17] Haáz I B. Relationship Between the Potential of the Attraction of the Mass Contained in a Finite Rectangular Prism and Its First and Second Derivatives[J]. Geophysical Transactions, 1953, 2:57-66.
[18] Zhdanov M S. GeophysicalInverse Theory and Re-gularization Problems[M].Salt Lake:Elsevier Science, 2002:51-57.
[19] Szymczyk M, Szymczyk P. Matlab and Parallel Computing[J]. Image Processing & Communications, 2014, 17(4):207-216.
[20] Oliveira V C Jr, Barbosa V C F. 3-D Radial Gravity Gradient Inversion[J]. Geophysical Journal International, 2013, 195(2):883-902.
[21] Geng M, Huang D, Yang Q, et al. 3D Inversion of Airborne Gravity-Gradiometry Data Using Cokriging[J]. Geophysics, 2014, 79(4):G37-G47.
[22] Wang T H, Huang D N, Ma G Q, et al. Improved Preconditioned Conjugate Gradient Algorithm and Application in 3D Inversion of Gravity-Gradiometry Data[J]. Applied Geophysics,2017, 14(2):301-313.
[23] Ennen C. Structural Mapping of the Vinton Salt Dome, Louisiana, Using Gravity Gradiometry Data[J]. Seg Technical Program Expanded Abstracts, 2011, 30(1):830-835.
[24] Marfurt K J, Zhou H W, Sullivan E C. Development and Calibration of New 3-D Vector Vsp Imaging Technology:Vinton Salt Dome, LA[R]. Houston:University of Houston, 2004.
[1] 殷文. 基于频率域高阶有限差分法的正演模拟及并行算法[J]. J4, 2008, 38(1): 144-0151.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
版权所有 © 《吉林大学学报(地球科学版)》编辑部
地址：长春市西民主大街938号(130026)　电话：+86-431-88502374；13756165364　E-mail: xuebao1956@jlu.edu.cn
本系统由北京玛格泰克科技发展有限公司设计开发