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Application of nonlinear methods to inversion of 1D magnetotelluric sounding data based on very fast simulated annealing

Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The inversion of geophysical data depends on the availability of a priori information on the geology of the earth inversion method chosen, and the appropriate definition of parameters of the model. Traditionally, 1D magnetotelluric data have been inverted by the trial-and-error method, which employs iterated, linearized inversion methods. However, this approach involves a good knowledge of parameters of the analyzed earth. Unlike the linearized inversion, the nonlinear inversion does not depend so much on a starting model; however, a proper choice of the starting model can reduce the time and cost of computation. In this paper the authors applied a nonlinear optimization method, called very fast simulated annealing (VFSA), to one-dimensional inversion of magnetotelluric sounding data. The authors made some simplified assumption concerning the selection of cooling constants and reducing the equivalence of geoelectric models. The inversion was performed in three ways: the individual inversion of amplitude data, individual inversion of phase data, and joint inversion of amplitude and phase data.
Rocznik
Strony
307--322
Opis fizyczny
Bibliogr. 14 poz.
Twórcy
autor
  • University of Mining and Metallurgy, al. Mickiewicza 30, 30-059 Kraków, Poland
  • Geophysical Exploration Company ul. Jagiellońska 76, 03-301 Warszawa, Poland
autor
  • University of Mining and Metallurgy, al. Mickiewicza 30, 30-059 Kraków, Poland
  • Geophysical Exploration Company ul. Jagiellońska 76, 03-301 Warszawa, Poland
autor
  • University of Mining and Metallurgy, al. Mickiewicza 30, 30-059 Kraków, Poland
Bibliografia
  • 1. Chunduru, R.K., M.K. Sen and P.L. Stoffa, 1996, 2-D resistivity inversion using spline parametrization and simulated annealing, Geophysics 61, l, 151-161.
  • 2. Constable, S.C., R.L. Parker and C.G. Constable, 1987, Occam's inversion: A practical algorithm for generating smooth models from electromagnetic sounding data, Geophysics 52, 3, 289-300.
  • 3. Dosso, S.E., and D.W. Oldenburg, 1991, Magnetotelluric appraisal using simulated annealing, Geophys. J. Int. 106, 370-386.
  • 4. Jupp, D.L.B., and K. Vozoff, 1975, Stable iterative methods for the inversion of geophysical data, Geophys. J. astron. Soc. 42, 3, 957-976.
  • 5. Metropolis, N., A. Rosenbluth, M. Rosenbluth, A. Teller and E. Teller, 1953, Equation of state calculations by fast computing machines, J. Chem. Phys. 21, 6, 1087-1092.
  • 6. Rodi, W., and R.L. Mackie, 2001, Nonlinear conjugate gradients algorithm for 2-D magnetotelluric inversion, Geophysics 66, l, 174-187.
  • 7. Sen, M.K., B.B. Bhattacharya and P.L. Stoffa, 1993, Nonlinear inversion of resistivity sounding data, Geophysics 58, 4, 496-507.
  • 8. Sen, M.K., and P.L. Stoffa, 1991, Nonlinear one-dimensional seismic wave inversion using simulated annealing, Geophysics 56, 1624-1638.
  • 9. Sharma, S.P., and P. Kaikkonen, 1998, Two-dimensional non-linear inversion of YLF-R data using simulated annealing, Geophys. J. Int. 133, 649-668.
  • 10. Smith, J.T., and J.R. Booker, 1988, Magnetotelluric inversion for minimum structure, Geophysics 53, 1565-1576.
  • 11. Syaripudin, A., and H. Grandis, 2001, Inversi Data Magnetotelluric 1-D Menggunakan Metoda Simulated Annealing, Kontribusi Fisika Indonesia 12, 2.
  • 12. Vasudevan, K., W.G. Wilson and W.G. Laidlaw, 1991, Simulated annealing statics computation using an order-based energy function, Geophysics 56, 11, 1831-1839.
  • 13. Welis, D.R., and T.J. Ulrych, 1996, Simulated annealing wavelet estimation via fourth-order cumulant matching, Geophysics 61, 6, 1939-1948.
  • 14. Wu, F.T., 1968, The inverse problem of magnetotelluric sounding, Geophysics 33, 6, 912-919
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BSL7-0007-0049
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