1887
  1. Home
  2. A-Z Publications
  3. Geophysical Prospecting
  4. Volume 63, Issue 1
  5. Article
Volume 63 Number 1
  • E-ISSN: 1365-2478

Abstract

ABSTRACT

Time‐domain electromagnetic data are conveniently inverted by using smoothly varying 1D models with fixed vertical discretization. The vertical smoothness of the obtained models stems from the application of Occam‐type regularization constraints, which are meant to address the ill‐posedness of the problem. An important side effect of such regularization, however, is that horizontal layer boundaries can no longer be accurately reproduced as the model is required to be smooth. This issue can be overcome by inverting for fewer layers with variable thicknesses; nevertheless, to decide on a particular and constant number of layers for the parameterization of a large survey inversion can be equally problematic.

Here, we present a focusing regularization technique to obtain the best of both methodologies. The new focusing approach allows for accurate reconstruction of resistivity distributions using a fixed vertical discretization while preserving the capability to reproduce horizontal boundaries. The formulation is flexible and can be coupled with traditional lateral/spatial smoothness constraints in order to resolve interfaces in stratified soils with no additional hypothesis about the number of layers. The method relies on minimizing the number of layers of non‐vanishing resistivity gradient, instead of minimizing the norm of the model variation itself. This approach ensures that the results are consistent with the measured data while favouring, at the same time, the retrieval of horizontal abrupt changes. In addition, the focusing regularization can also be applied in the horizontal direction in order to promote the reconstruction of lateral boundaries such as faults.

We present the theoretical framework of our regularization methodology and illustrate its capabilities by means of both synthetic and field data sets. We further demonstrate how the concept has been integrated in our existing spatially constrained inversion formalism and show its application to large‐scale time‐domain electromagnetic data inversions.

Copyright © 2015 European Association of Geoscientists & Engineers © 2014 European Association of Geoscientists & Engineers
Loading

Article metrics loading...

/content/journals/10.1111/1365-2478.12185
2014-12-01
2024-04-26

  • From This Site

    /content/journals/10.1111/1365-2478.12185
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Journal -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. ÁrnasonK.2008. A Short Manual for the Program TEMDDD. The National Energy Authority of Iceland, Reykjavík, Iceland.
     [Google Scholar]
  2. AukenE. and ChristiansenA.V.2004. Layered and laterally constrained 2D inversion of resistivity data. Geophysics69, 752–761.
     [Google Scholar]
  3. AukenE., ChristiansenA.V., JacobsenB.H., FogedN. and SørensenK.I.2005. Piecewise 1D laterally constrained inversion of resistivity data. Geophysical Prospecting53, 497–506.
     [Google Scholar]
  4. AukenE., ChristiansenA.V., JacobsenL. and SørensenK.I.2008. A resolution study of buried valleys using laterally constrained inversion of TEM data. Journal of Applied Geophysics65, 10–20.
     [Google Scholar]
  5. AukenE., ChristiansenA.V., WestergaardJ.A., KirkegaardC., FogedN. and ViezzoliA.2009. An integrated processing scheme for high‐resolution airborne electromagnetic surveys, the SkyTEM system. Exploration Geophysics40, 184–192.
     [Google Scholar]
  6. BehroozmandA.A., AukenE., FiandacaG. and ChristiansenA.V.2012a. Improvement in MRS parameter estimation by joint and laterally constrained inversion of MRS and TEM data. Geophysics74, WB191–WB200.
     [Google Scholar]
  7. BehroozmandA.A., AukenE., FiandacaG., and ChristiansenA.V. and ChristensenN.B.2012b. Efficient full decay inversion of MRS data with a stretched‐exponential approximation of the inline image T2*distribution. Geophysical Journal International190, 900–912.
     [Google Scholar]
  8. BlaschekR., HördtA. and KemnaA.2008. A new sensitivity‐controlled focusing regularization scheme for the inversion of induced polarization data based on the minimum gradient support. Geophysics73, F45–F54.
     [Google Scholar]
  9. BrodieR.2010. Holistic inversion of airborne electromagnetic data. PhD thesis, The Australian National University, Australia.
     [Google Scholar]
  10. BrodieR. and SambridgeM.2006. A holistic approach to inversion of frequency‐domain airborne EM data. Geophysics71, G301–G312.
     [Google Scholar]
  11. ChristensenN.B. and TølbøllR.J.2009. A lateral model parameter correlation procedure for one‐dimensional inverse modelling. Geophysical Prospecting57, 919–929.
     [Google Scholar]
  12. ChristiansenA.V. and AukenE.2012. A global measure for depth of investigation. Geophysics77, WB171–WB177.
     [Google Scholar]
  13. ConstableS.C., ParkerR.L. and ConstableC.G.1987. Occam's inversion: a practical algorithm for generating smooth models from electromagnetic sounding data. Geophysics52, 289–300.
     [Google Scholar]
  14. CoxL.H., WilsonG.A. and ZhdanovM.S.2010. 3D inversion of airborne electromagnetic data using a moving footprint. Exploration Geophysics41, 250–259.
     [Google Scholar]
  15. FiandacaG., AukenE., GazotyA. and ChristiansenA.V.2012. Time‐domain induced polarization: full‐decay forward modeling and 1D laterally constrained inversion of Cole‐Cole parameters. Geophysics77, E213–E225.
     [Google Scholar]
  16. FiandacaG., RammJ., BinleyA., GazotyA., ChristiansenA.V. and AukenE.2013. Resolving spectral information from time domain induced polarization data through 2‐D inversion. Geophysical Journal International192, 631–646.
     [Google Scholar]
  17. GuillemoteauJ., SailhacP. and BehaegelM.2012. Fast approximate 2D inversion of airborne TEM data: Born approximation and empirical approach. Geophysics77, WB89–WB97.
     [Google Scholar]
  18. HaberE., OldenburgD.W. and ShekhtmanR.2007. Inversion of time domain three‐dimensional electromagnetic data. Geophysical Journal International171, 550–564.
     [Google Scholar]
  19. HarboM.S., PedersenJ., JohnsenR. and PetersenK.2011. Groundwater in a Future Climate . ISBN: 87–7788–265–2
  20. JørgensenF., ScheerW., ThomsonS., SonnenborgT.O., HinsbyK., WiederholdH.et al. 2012. Transboundary geophysical mapping of geological elements and salinity distribution critical for the assessment of future sea water intrusion in response to sea level rise. Hydrology and Earth System Sciences16, 1845–1862.
     [Google Scholar]
  21. MarquartD.1963. An algorithm for least squares estimation of nonlinear parameters. SIAM Journal of Applied Mathematics11, 431–441.
     [Google Scholar]
  22. Monteiro SantosF.A.2004. 1‐D laterally constrained inversion of EM34 profiling data. Journal of Applied Geophysics56, 123–134.
     [Google Scholar]
  23. NewmanG. and CommerM.2005. New advances in three dimensional transient electromagnetic inversion. Geophysical Journal International160, 5–32.
     [Google Scholar]
  24. NewmanG.A., AndersonW.L. and HohmannG.W.1987. Interpretation of transient electromagnetic soundings over three‐dimensional structures for the central‐loop configuration. Geophysical Journal of The Royal Astronomical Society89, 889–914.
     [Google Scholar]
  25. PagliaraG. and VignoliG.2006. Focusing inversion techniques applied to electrical resistance tomography in an experimental tank. International Association for Mathematical Geology XI International Congress Processing.
     [Google Scholar]
  26. PortniaguineO. and ZhdanovM.S.1999. Focusing geophysical inversion images. Geophysics64, 874–887.
     [Google Scholar]
  27. SasakiY.2001. Full 3‐D inversion of electromagnetic data on PC. Journal of Applied Geophysics46, 45–54.
     [Google Scholar]
  28. SasakiY.N.H.2003. Topographic effects in frequency‐domain helicopterborne electromagnetics. Exploration Geophysics34, 24–28.
     [Google Scholar]
  29. SengpielK.P. and SiemonB.2000. Advanced inversion methods for airborne electromagnetic exploration. Geophysics65, 1983–1992.
     [Google Scholar]
  30. SørensenK.I. and AukenE.2004. SkyTEM – A new high‐resolution helicopter transient electromagnetic system. Exploration Geophysics35, 191–199.
     [Google Scholar]
  31. TikhonovA.N. and ArseninY.V.1977. Solution of Ill‐Posed Problems. Winston & Sons. ISBN 0–470–99124–0.
     [Google Scholar]
  32. TriantafilisJ. and Monteiro SantosF.A.2009. 2‐dimensional soil and vadose zone representation using an EM38 and EM34 and a laterally constrained inversion model. Australian Journal of Soil Research47, 809–820.
     [Google Scholar]
  33. ValléeM.A. and SmithR.S.2009. Inversion of airborne time‐domain electromagnetic data to a 1D structure using lateral constraints. Near Surface Geophysics7, 63–71.
     [Google Scholar]
  34. ViezzoliA., ChristiansenA.V., AukenE. and SørensenK.I.2008. Quasi‐3D modeling of airborne TEM data by spatially constrained inversion. Geophysics73, F105–F113.
     [Google Scholar]
  35. ViezzoliA., MundayT., AukenE. and ChristiansenA.V.2010. Accurate quasi 3D versus practical full 3D inversion of AEM data – the Bookpurnong case study. Preview149, 23–31.
     [Google Scholar]
  36. VignoliG. and CassianiG.2010. Identification of lateral discontinuities via multi‐offset phase analysis of surface wave data. Geophysical Prospecting58, 389–413.
     [Google Scholar]
  37. VignoliG., CassianiG. and DeianaR.2012. Focused inversion of vertical radar profile (VRP) traveltime data. Geophysics77, H9–H18.
     [Google Scholar]
  38. VignoliG., StrobbiaC., CassianiG. and VermeerP.2011. Statistical multi‐offset phase analysis (sMOPA) for surface wave processing in laterally varying media. Geophysics76, U1–U11.
     [Google Scholar]
  39. WilsonG.A., RaicheA. and SugengF.2006. 2.5D inversion of airborne electromagnetic data. Exploration Geophysics37, 363–371.
     [Google Scholar]
  40. WisénR. and ChristiansenA.V.2005. Laterally and mutually constrained inversion of surface wave seismic data and resistivity data. Journal of Environmental & Engineering Geophysics10, 251–262.
     [Google Scholar]
  41. YangD. and OldenburgD.W.2012. Three‐dimensional inversion of airborne time‐domain electromagnetic data with applications to a porphyry deposit. Geophysics77, B23–B34.
     [Google Scholar]
  42. ZhdanovM.S.2002. Geophysical inverse theory and regularization problems. Elsevier. ISBN‐10: 0–444–51089–3.
     [Google Scholar]
  43. ZhdanovM.S. and TolstayaE.2004. Minimum support nonlinear parametrization in the solution of a 3D magnetotelluric inverse problem. Inverse Problems20, 937–952.
     [Google Scholar]
  44. ZhdanovM.S., VignoliG. and UedaT.2006. Sharp boundary inversion in crosswell traveltime tomography. Journal of Geophysics and Engineering3, 122–134.
     [Google Scholar]
http://instance.metastore.ingenta.com/content/journals/10.1111/1365-2478.12185
Loading
Sharp spatially constrained inversion with applications to transient electromagnetic data
Geophysical Prospecting 63, 243 (2015); https://doi.org/10.1111/1365-2478.12185
/content/journals/10.1111/1365-2478.12185
/content/journals/10.1111/1365-2478.12185
Loading

Data & Media loading...

  • Article Type: Research Article
Keyword(s): (Airborne) time‐domain EM; Focusing inversion; Lateral discontinuities; Sharp boundaries; Spatially constrained inversion

Most Cited This Month Most Cited RSS feed

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