The node physical property model with good sparseness is the difference form of its corresponding block physical property model. It can not only eliminate computational redundancy and improve the efficiency of forward computation, but also can effectively recover simple geology models. The developed gravity-magnetic simultaneous inversion method introduces the structure similarity constraint between two node physical property models to make the inversion results have the characteristics of structural consistency. The Cauchy norm constraint can be used to get a sparse solution. Within the conventional inversion framework, this strategy does not need to apply nonlinear functions such as physical property transformation function to overcome the problem of nonlinear enhancement, and the inversion results are not affected by the initial value. The model tests show that the inversion method can effectively recover simple geology models. The boundary of the recovered anomalies is clear and the location is close to the real position. The block physical property values of the recovered anomalies are also closer to their true values. Compared with the inversion using only one geophysical method data, the joint inversion improves the vertical resolution of anomalies to a certain extent, and inhibits the generation of partial interference anomalies.


Article metrics loading...

Loading full text...

Full text loading...


  1. BlakelyR.J.
    , 1995, Potential Theory in Gravity and Magnetic Applications: Cambridge University Press.
    [Google Scholar]
  2. GallardoL.A., MejuM.A.
    , 2004, Joint two-dimensional DC resistivity and seismic traveltime inversion with cross-gradients constraints: Journal of Geophysical Research-atmospheres, 109, B03311.
    [Google Scholar]
  3. GuoZ.H., GuanZ.N., XiongS.Q.
    , 2004, Cuboid ΔT and its gradient forward theoretical expressions without analytic odd points: Chinese Journal of Geophysics, 47(6), 1131–1138.
    [Google Scholar]
  4. Last, B. J., and K.Kubik
    , 1983, Compact gravity inversion: Geophysics, 48, 713–721.
    [Google Scholar]
  5. Li,Y., and OldenburgD.W.
    , 1996, 3-D inversion of magnetic data: Geophysics, 61, 394–408.
    [Google Scholar]
  6. Portniaguine, O., and ZhdanovM.S.
    , 1999, Focusing geophysical inversion images: Geophysics. 64, 1532–1541.
    [Google Scholar]
  7. Pilkington, M.
    , 2009, 3D magnetic data-space inversion with sparseness constrains: Geophysics, 74(1), L7–L15.
    [Google Scholar]
  8. ZhangS., MengX.H., ChenZ.X., and ZhouJ.J.
    , 2015, Rapid calculation of gravity anomalies based on residual node densities and its GPU implementation: Computers & Geosciences, 83, 139–145.
    [Google Scholar]

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error