1887

Abstract

Summary

We developed a 3D parametric inversion for time-domain airborne EM data using a skewed ellipsoid representation for multiple conductive or resistive anomalies. The approach aims to simplify the task of imaging thin, potentially highly conductive, anomalies with 3D EM inversion. The algorithm finds the optimal location, shape, size and resistivity of the anomalies in a homogeneous or heterogeneous background by employing a Gauss-Newton style optimization.

Our parametric method is tested on a synthetic and field data set. The synthetic model is composed of two narrow dipping conductive anomalies in a resistive background along with a vertical narrow conductor. The survey layout and resistivity structure is based off field data from a greenstone setting. The parametric inversion accurately recovers the spatial extent and dips of the three synthetic anomalies, although the depth extent of the anomalies is exaggerated. In the greenstone field example, the inversion defines the spatial location, extent and dips of three conductive anomalies to provide a new conductivity interpretation of an area where little information is known regarding the true nature of the conductors.

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/content/papers/10.3997/2214-4609.201413870
2015-09-06
2024-03-29
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References

  1. Aghasi, A., Kilmer, M. and Miller, E.L.
    [2011] Parametric level set methods for inverse problems. SIAM Journal on Imaging Sciences, 4, 618–650.
    [Google Scholar]
  2. Allard, M.
    [2007] On the origin of HTEM species. Proceedings of Exploration ’07, 355–373.
    [Google Scholar]
  3. Dorn, O., Miller, E.L. and Rappaport, C.M.
    [2000] A shape reconstruction method for electromagnetic tomography using adjoint fields and level sets. Inverse Problems, 16, 1119–1156.
    [Google Scholar]
  4. Haber, E. and Schwarzbach, C.
    [2014] Parallel inversion of large-scale airborne time-domain electromagnetic data with multiple OcTree meshes. Inverse Problems, 30, 1–28.
    [Google Scholar]
  5. Haber, E., Heldmann, S. and Ascher, U.
    [2007] Adaptive finite volume method for distributed non-smooth parameter identification. Inverse Problems, 23, 1659–1676.
    [Google Scholar]
  6. McMillan, M.S., Schwarzbach, C., Oldenburg, D.W., Haber, E., Holtham, E. and PrikhodkoA.
    [2014] Recovering a thin dipping conductor with 3D electromagnetic inversion over the Caber deposit. 84th Annual International Meeting, SEG, Expanded Abstracts, 1720–1724.
    [Google Scholar]
  7. Oldenburg, D.W., Haber, E. and Shekhtman, R.
    [2013] Three dimensional inversion of multisource time domain electromagnetic data. Geophysics, E47–E57.
    [Google Scholar]
  8. Osher, S. and Sethian, J.
    [1988] Fronts propagating with curvature dependent speed: algorithms based on Hamilton-Jacobi formulations. Journal of Computational Physics, 79, 12–49.
    [Google Scholar]
  9. Tai, X. and Chan, T.
    [2004] A survey on multiple level set methods with applications for identifying piecewise constant functions. International Journal of Numerical Analysis and Modeling, 1, 25–47.
    [Google Scholar]
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