1887

Abstract

Summary

This paper proposed a kind of correlation constraint based on sine function for joint inversion of gravity and magnetic data. This new constraint is developed by conventional linear correlation constraint, but has better stability. At the same time, considering that the density contrast and magnetic contrast of the geological anomalies are not always of same sigh, which causes the density model and the magnetic model to be locally correlated but not globally correlated, we used the square of the density and the square of the magnetic instead of the density and the magnetic parameter to define the proposed correlation constraint. Then we gave the explicit form of the derivative of the proposed constraint with respect to the weighted density and magnetic parameter, which makes it easy to obtain the optimal solution of the objective function by the conjugate gradient algorithm in the weighted parameter domain. The method was applied to one model test to verify the feasibility.

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/content/papers/10.3997/2214-4609.201901056
2019-06-03
2024-03-28
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References

  1. FregosoE., GallardoL.A.
    , 2009. Cross-gradient joint 3D inversion with applications to gravity and magnetic data. Geophysics, 74(4): L31–L42.
    [Google Scholar]
  2. Gallardo, L. A., & Meju, M. A.
    , 2003. Characterization of heterogeneous near-surface materials by joint 2D inversion of dc resistivity and seismic data. Geophysical Research Letters, 30(13).
    [Google Scholar]
  3. GaoX., HuangD.
    , 2017. Research on 3D focusing inversion of gravity gradient data based on a conjugate gradient algorithm. Chinese J. Geophys. (in Chinese), 60(4): 1571–1583.
    [Google Scholar]
  4. Last, B. J., & Kubik, K.
    , 1983. Compact gravity inversion. Geophysics, 48(6), 713–721.
    [Google Scholar]
  5. Li, Y., & Oldenburg, D. W.
    , 1996. 3-D inversion of magnetic data. Geophysics, 61(2), 394–408.
    [Google Scholar]
  6. Lin, W., & Zhdanov, M. S.
    , 2018. Joint multinary inversion of gravity and magnetic data using Gramian constraints. Geophysical Journal International, 215(3), 1540–1557.
    [Google Scholar]
  7. Oldenburg, D. W., & Li, Y.
    , 1999. Estimating depth of investigation in dc resistivity and IP surveys. Geophysics, 64(2), 403–416.
    [Google Scholar]
  8. PeterG. L., ColinG. F., and CharlesA. H.
    , 2012. Joint inversion of seismic travel times and gravity data on unstructured grids with application to mineral exploration. Geophysics, 77(1): K1–K15.
    [Google Scholar]
  9. Portniaguine, O., & Zhdanov, M. S.
    , 2002. 3-D magnetic inversion with data compression and image focusing. Geophysics, 67(5), 1532–1541.
    [Google Scholar]
  10. Shi, B., Yu, P., Zhao, C., Zhang, L., & Yang, H.
    (2018). Linear correlation constrained joint inversion using squared cosine similarity of regional residual model vectors. Geophysical Journal International, 215(2), 1291–1307.
    [Google Scholar]
  11. Silva, J. B., Medeiros, W. E., & Barbosa, V. C.
    , 2000. Gravity inversion using convexity constraint. Geophysics, 65(1), 102–112.
    [Google Scholar]
  12. Sun, J., & Li, Y.
    , 2016. Joint inversion of multiple geophysical data using guided fuzzy c-means clustering. Geophysics, 81(3), ID37–ID57.
    [Google Scholar]
  13. Tikhonov, A. N., & Arsenin, V. Y.
    , 1977. Methods for solving ill-posed problems (p. 12). John Wiley and Sons, Inc.
    [Google Scholar]
  14. YinC. C., SunS. Y., GaoX. H.
    , 2018. 3D joint inversion of magnetotelluric and gravity data based on local correlation constraints. Chinese J. Geophys. (in Chinese), 61(1):358–367.
    [Google Scholar]
  15. Zhdanov, M. S., Gribenko, A., & Wilson, G.
    , 2012. Generalized joint inversion of multimodal geophysical data using Gramian constraints. Geophysical Research Letters, 39(9).
    [Google Scholar]
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