Advanced Search
  • 全国中文核心期刊
  • 中国科技核心期刊
  • 美国工程索引（EI）收录期刊
  • Scopus数据库收录期刊
Volume 36 Issue 7
Turn off MathJax
Article Contents
Abstract
References
LIU Bin, WANG Chuan-wu, YANG Wei-min, LI Shu-cai, NIE Li-chao, SONG Jie. 3D resistivity inversion using improved parallel genetic algorithm[J]. Chinese Journal of Geotechnical Engineering, 2014, 36(7): 1252-1261. DOI: 10.11779/CJGE201407009
Citation: LIU Bin, WANG Chuan-wu, YANG Wei-min, LI Shu-cai, NIE Li-chao, SONG Jie. 3D resistivity inversion using improved parallel genetic algorithm[J]. Chinese Journal of Geotechnical Engineering, 2014, 36(7): 1252-1261. DOI: 10.11779/CJGE201407009
shu

3D resistivity inversion using improved parallel genetic algorithm

  • Research Center of Geotechnical & Structural Engineering, Shandong University, Jinan 250061, China

More Information
  • Received Date: October 04, 2013
  • Published Date: July 24, 2014
    Graphical Abstract
    • Abstract
  • The low calculation efficiency of the genetic algorithm (GA) method is an obstacle to 3D resistivity inversion. Moreover, some improved methods which are time-consuming but beneficial for the inversion effect and the search efficiency can not be used in GA due to their low calculation efficiencies. To solve the above problems, a multi-level master-slave parallel computing strategy for GA is put forward based on the natural characteristics of parallel computing. Through this improvement, a generating method for strictly uniform initial population is proposed, with which the initial generation can be closer to the optimal solution. A random-ratio arithmetical crossover algorithm is proposed based on the differences of fitness values between the cross-individuals, which can keep genetic competition advantages of the better individual. Then the joint mutation algorithm is presented, which is the combination of the traditional random mutation algorithm and the deterministic search optimization algorithm in the linear inversion. It can maintain the randomness of the mutation and optimize the mutation direction. Eventually a 3D resistivity inversion using an improved parallelized GA is formed. The performance of the improved parallel GA is evaluated in synthetic and practical cases. The examples illustrate that the improved parallel GA can enhance the calculation efficiency significantly and has obvious advantages in searching the optimal solution, suppressing the false anomaly and obtaining high-quality inversion results. The improved parallel GA provides an effective way for 3D resistivity inversion imaging in practical projects.
    • FullText(HTML)
    • References (33)
  • [1]
    SASAKI Yutaka. 3D resisitivity inversion using the finite- element method[J]. Geophysics, 1994, 59(11): 1839-1848.
    [2]
    黄俊革, 阮百尧, 鲍光淑. 基于有限单元法的三维地电断面电阻率反演[J]. 中南大学学报(自然科学版), 2004, 35(2): 295-299. (HUANG Jun-ge, RUAN Bai-yao, BAO Guang-shu. Resistivity inversion on 3D section based on FEM[J]. Journal of Central South University (Natural Science), 2004, 35(2): 295-299. (in Chinese))
    [3]
    底青云, 王妙月. 积分法三维电阻率成像[J]. 地球物理学报, 2001, 44(6): 843-852. (DI Qing-yun, WANG Miao-yue. 3-D resistivity tomography by integral method[J]. Chinese Journal of Geophysics, 2001, 44(6): 843-852. (in Chinese))
    [4]
    ZHANG Jie, RANDALL L Mackie, THEODORE R. Madden.3-D resistivity forward modeling and inversion using conjugate gradients[J]. Geophysics, 2008, 60(5): 1313-1325.
    [5]
    吴小平, 徐果明. 利用共轭度法的电阻率三维反演研究[J].地球物理学报, 2000, 43(3): 420-426. (WU Xiao-ping, XU Guo-ming. Study on 3D resistivity inversion using conjugate gradient method[J]. Chinese Journal of Geophysics, 2000, 43(3): 420-426. (in Chinese))
    [6]
    宛新林, 席道瑛, 高尔根, 等. 用改进的光滑约束最小二乘正交分解法实现电阻率三维反演[J]. 地球物理学报, 2005, 48(1): 439-444. (WAN Xin-lin, XI Dao-ying, GAO Er-gen, et al. 3-D resistivity inversion by the least-squares QR factorization method under improved smoothness constraint condition[J]. Chinese Journal of Geophysics, 2005, 48(1): 439-444. (in Chinese))
    [7]
    刘 斌, 李术才, 李树忱, 等. 基于不等式约束的最小二乘法三维电阻率反演及其算法优化[J]. 地球物理学报, 2012, 55(1): 260-268. (LIU Bin, LI Shu-cai, LI Shu-chen, et al. 3D electrical resistivity inversion with least-squares method based on inequality constraint and its computation efficiency optimization[J]. Chinese Journal of Geophysics, 2012, 55(1): 260-268. (in Chinese))
    [8]
    刘 斌, 李术才, 聂利超, 等. 基于自适应加权光滑约束与PCG算法的三维电阻率探测反演成像[J]. 岩土工程学报, 2012, 34(9): 1646-1653. (LIU Bin, LI Shu-cai, NIE Li-chao, et al. Inversion imaging of 3D resistivity detection using adaptive-weighted smooth constraint and PCG algorithm[J]. Chinese Journal of Geotechnical Engineering, 2012, 34(9): 1646-1653. (in Chinese))
    [9]
    JIMMY Stephen, MANOJ C, SINGH S B. A direct inversion scheme for deep resistivity sounding data using artificial neural networks[J]. Journal of Earth System Science, 2004, 113(1): 49-66.
    [10]
    SINGH U K, TIWARI R K, SINGH S B. One-dimensional inversion of geo-electrical resistivity sounding data using artificial neural networks—a case study[J]. Computers & Geosciences, 2005, 31(1): 99-108.
    [11]
    SINGH U K, TIWARI R K, SINGH S B. Inversion of 2-D DC resistivity data using rapid optimization and minimal complexity neural network[J]. Nonlin Processes Geophys, 2010, 17: 65-76.
    [12]
    徐海浪, 吴小平. 电阻率二维神经网络反演[J]. 地球物理学报, 2006, 49(2): 584-589. (XU Hai-lang, WU Xiao-ping. 2D resistivity inversion using the neural network method[J]. Chinese Journal of Geophysics, 2006, 49(2): 584-589. (in Chinese))
    [13]
    EL-QADY G, USHIJIMA K. Inversion of DC resistivity data using neural networks[J]. Geophysical Prospecting, 2001, 49: 417-430.
    [14]
    DITTMER J K, SZYMANSKI J E. The stochastic inversion of magnetic and resistivity data using the simulated annealing algorithm[J]. Geophysical Prospecting, 1995, 43: 397-416.
    [15]
    卢元林, 王兴泰, 王 若, 等. 电阻率成像反演中的模拟退火方法[J]. 地球物理学报, 1999, 42(增刊1): 225-233. (LU Yuan-lin, WANG Xing-tai, WANG Ruo, et al. The simulated annealing method of electrical resistivity tomography[J]. Chinese Journal of Geophysics, 1999, 42(S1): 225-233. (in Chinese))
    [16]
    CHUNDURU R K, SEN M K, STOFFA P L, et al. Nonlinear inversion of resistivity profiling data for some regular geometrical bodies[J]. Geophysical Prospecting, 1995, 43(8): 979-003.
    [17]
    CHUNDURU R K, SEN M K, STOFFA P L. 2-D resistivity inversion using spline parameterization and simulated annealing[J]. Geophysics, 1996, 61(1): 151-161.
    [18]
    SEN M K, BHATTACHARYA B B, STOFFA P L. Nonlinear inversion of resitivity sounding data[J]. Geophysics, 1993, 58(4): 496-507.
    [19]
    王兴泰, 李晓芹, 孙仁国. 电测深曲线的遗传算法反演[J].地球物理学报, 1996, 39(2): 279-285. (WANG Xing-tai, LI Xiao-qin, SUN Ren-guo. The inversion of resistivity sounding curve using genetic algorithm[J]. Chinese Journal of Geophysics, 1996, 39(2): 279-285. (in Chinese))
    [20]
    李帝铨, 王光杰, 底青云, 等. 基于遗传算法的CSAMT最小构造反演[J]. 地球物理学报, 2008, 51(4): 1234-1245. (LI Di-quan, WANG Guang-jie, DI Qing-yun, et al. The application of Genetic Algorithm to CSAMT inversion for minimum structure[J]. Chinese Journal of Geophysics, 2008, 51(4): 1234-1245. (in Chinese))
    [21]
    MADAN K Jha, KUMAR S, CHOWDHURY A. Vertical electrical sounding survey and resistivity inversion using genetic algorithm optimization technique[J]. Journal of Hydrology, 2008, 359: 71-87.
    [22]
    闫永利, 陈本池, 赵永贵, 等. 电阻率层析成像非线性反演[J]. 地球物理学报, 2009, 52(3): 758-764. (YAN Yong-li, CHEN Ben-chi, ZHAO Yong-gui, et al. Nonlinear inversion for electrical resistivity tomography[J]. Chinese Journal of Geophysics, 2009, 52(3): 758-764. (in Chinese))
    [23]
    BAŞOKUR A T, AKCA I. Object-based model verification by a genetic algorithm approach: Application in archeological targets[J]. Journal of Applied Geophysics, 2011, 74(4): 167-174.
    [24]
    BOSCHETTI F, DENTITH M C, LIST R D. Inversion of potential field data by Genetic Algorithms[J]. Geophysical Prospecting, 1997, 45(3): 461-478.
    [25]
    LIU B, LI S C, NIE L C, et al. 3D resistivity inversion using an improved Genetic Algorithm based on control method of mutation direction[J]. Journal of Applied Geophysics, 2012, 87: 1-8.
    [26]
    王小平, 曹立明. 遗传算法——理论、应用与软件实现[M]. 西安: 西南交通大学出版社, 2002. (WANG Xiao-ping, CAO Li-ming. Genetic algorithm—theory, application and software[M]. Xi'an: Xi'an Jiaotong University Press, 2002. (in Chinese))
    [27]
    姚磊华, 李竞生. 综合改进的遗传算法反演三维地下水流模型参数[J]. 岩石力学与工程学报, 2004, 23(4): 625-630. (YAO Hua-lei, LI Jing-sheng. Parameters identification of 3D groundwater flow model with improved genetic algorithm[J]. Chinese Journal of Rock Mechanics and Engineering, 2004, 23(4): 625-630. (in Chinese))
    [28]
    刘耀儒, 杨 强, 刘福深, 等. 基于并行改进遗传算法的拱坝位移反分析[J]. 清华大学学报( 自然科学版), 2006, 46(9): 1542-1550. (LIU Yao-ru, YANG Qiang, LIU Fu-shen, et al. Inverse analyses of arch dam displacements using improved parallel genetic algorithm[J]. Journal of TSinghua University (Science and Technology), 2006, 46(9): 1542-1550. (in Chinese))
    [29]
    张志增, 李仲奎, 程丽娟. 基于主从式并行遗传算法的岩土力学参数反分析方法[J]. 工程力学, 2010, 27(10): 21-26. (ZHANG Zhi-zeng, LI Zhong-kui, CHENG Li-juan. Back analysis on geomechanical parameters based on a master-slave parallel genetic algorithm[J]. Engineering Mechanics, 2010, 27(10): 21-26. (in Chinese))
    [30]
    何大阔, 王福利, 贾明兴. 遗传算法初始种群与操作参数的均匀设计[J]. 东北大学学报: 自然科学版, 2005, 26(9): 828-831. (HE Da-kuo, WANG Fu-li, JIA Ming-xing. Uniform design of initial population and operatinal parameters of genetic algorithm[J]. Journal of Northeastern University: Natural Science, 2005, 26(9): 828-831. (in Chinese))
    [31]
    雷 轶, 菊 覃, 红邹娜. 折叠反转设计的中心化L: 偏差值的一些下界[J]. 数学物理学报, 2010, A30(6): 1555-1561. (LEI Y J, QIN H, ZOU N. Some lower bounds of centered L2-discrepancy on foldover designs[J]. Acta Mathematica Scientia, 2010, A30(6): 1555-1561. (in Chinese))
    [32]
    谭桂华, 聂建新, 杜 祥, 等. 小生境遗传算法在井间走时地震层析成像中的应用[J]. 工程力学, 2004, 21(4): 97-100. (TAN Gui-hua, NIE Jian-xin, DU Xiang, et al. Crosshole seismic velocity tomography based on niche genetic algorithms and QLTI[J]. Engineering Mechanics, 2004, 21(4): 97-100. (in Chinese))
    [33]
    刘 斌. 基于电阻率法与激电法的隧道含水地质构造超前探测与突水灾害实时监测研究[D]. 济南: 山东大学, 2010. (LIU Bin. Study on the water-bearing structure advanced detection and water inrush hazards real-time monitoring in tunnel based on the electrical resistivity method and induced polarization method[D]. Jinan: Shandong University, 2010. (in Chinese))
    • Related Articles
  • Supplements (0)

Catalog

    Get Citation
    PDF
    XML
    Article views (511) PDF downloads (377) Cited by()
    Related
    Copyright © 2010 Editorial By Chinese Journal of Geotechnical Engineering 苏ICP备05007122号-11公安联网备案号：32010602011255
    Editorial Office address：34 Hujuguan,Nanjing 210024,ChinaPostal Code：210024Tel：025-85829534，85829556E-mail: ge@nhri.cn

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return