• DocumentCode
    675372
  • Title

    Nanoparticles for electromagnetic fields enhancement in cross well imaging of subsurface

  • Author

    Wenji Zhang ; Qing Huo Liu

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Duke Univ., Durham, NC, USA
  • fYear
    2013
  • fDate
    7-13 July 2013
  • Firstpage
    197
  • Lastpage
    197
  • Abstract
    Summary form only given. During the past two decades there has been increasing interest in the cross well imaging of the subsurface for oil exploration applications. As more and more deviated and horizontal wells are drilled in an attempt to increase the oil production, the azimuthal symmetry no longer holds. Up to present, many numerical methods have been developed for the forward modeling of 3-D cross well logging, including the finite element method (C. Li, B. Xiong, and Y. Lv, Geophysical and Geochemical Exploration, 36, 585-590, 2012), stabilized biconjugate gradient fast Fourier transform method (BCGS-FFT) (Z. Q. Zhang, and Q. H. Liu, Trans. Geosci. and Remote Sens., 41, 998-1104, 2003) and extended Born approximation (H. Tseng and K. Lee, Twenty-Ninth Workshop on Geothermal Reservoir Engineering, 2004).
  • Keywords
    computational electromagnetics; conjugate gradient methods; electromagnetic fields; fast Fourier transforms; finite element analysis; nanoparticles; oil technology; well logging; 3D cross well logging; BCGS-FFT; azimuthal symmetry; cross well subsurface imaging; electromagnetic fields enhancement; extended Born approximation; finite element method; horizontal wells; nanoparticles; oil exploration; stabilized biconjugate gradient fast Fourier transform method; Computational modeling; Conductivity; Electromagnetic fields; Nanoparticles; Permeability; Reservoirs; Solid modeling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Radio Science Meeting (Joint with AP-S Symposium), 2013 USNC-URSI
  • Conference_Location
    Lake Buena Vista, FL
  • Print_ISBN
    978-1-4799-1128-8
  • Type

    conf

  • DOI
    10.1109/USNC-URSI.2013.6715503
  • Filename
    6715503