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3D magnetic inversion by planting anomalous den...

3D magnetic inversion by planting anomalous densities

Leonardo Uieda

May 15, 2013
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  1. Leonardo Uieda Valéria C. F. Barbosa Observatório Nacional - Brazil

    3D magnetic inversion by planting anomalous densities 2013 AGU Meeting of the Americas
  2. Leonardo Uieda Valéria C. F. Barbosa Observatório Nacional - Brazil

    3D magnetic inversion by planting anomalous densities 2013 AGU Meeting of the Americas
  3. Leonardo Uieda Valéria C. F. Barbosa Observatório Nacional - Brazil

    3D magnetic inversion by planting anomalous magnetization 2013 AGU Meeting of the Americas
  4. (Short) History of planting inversion • Uieda and Barbosa (early

    2012) based on René (1986) • For gravity and gradients • Deal with computational difficulties – A lot of data – Large meshes • A way to input geologic/geophysical information • Improvements at SEG 2012
  5. Why it grows that way • Choice of the best:

    1. Not random 2. 3. Smallest goal function φ=[∑ i (d i o−d i )2 ]1 2 Γ=ψ+μθ
  6. Γ=ψ+μθ θ=∑ k l k regularizing function compactness distance of

    added cells to seed ψ=[∑ i (α d i o−d i )2]1 2 shape-of-anomaly function (René, 1986) scale factor between observed and predicted = scalar μ
  7. Geologic profile Forward modeling After Dutra and Marangoni (2009) Layered

    complex Magnetization Dunite center Know the magnetization
  8. N

  9. N

  10. Use data weights φ=[∑ i w i (d i o−d

    i )2]1 2 w i =exp (−[(x i −x s )2+( y i −y s )2]2 σ4 )
  11. Use data weights φ=[∑ i w i (d i o−d

    i )2]1 2 w i =exp (−[(x i −x s )2+( y i −y s )2]2 σ4 ) s = closest seed
  12. Use data weights φ=[∑ i w i (d i o−d

    i )2]1 2 w i =exp (−[(x i −x s )2+( y i −y s )2]2 σ4 ) s = closest seed
  13. N

  14. Conclusion • Fast geometry estimation • Known magnetization • Seed

    position • Data weights = more robust • Magnetization of A2 ≠ ME – Probably higher