1887
Volume 23, Issue 1
  • ISSN: 1569-4445
  • E-ISSN: 1873-0604

Abstract

Abstract

This paper presents a fast hybrid inversion procedure for ground conductivity data. The frequency domain data from these instruments are close to obeying the low‐frequency approximation, however, not infrequently need to be treated in the QuasiStatic approximation with full induction. In this paper, we suggest a hybrid inversion approach consisting of three steps: the first one is an inversion in the low‐frequency approximation to assess the overall conductivity regime; followed by an inversion step in the Born approximation with a non‐zero half‐space reference model; the final inversion step is an accurate inversion in the QuasiStatic approximation. The first step is fully linear, while the next approach is a linearization of the first step of a full iterative inversion. The final inversion step uses full‐accuracy forward responses and approximate derivatives.

This hybrid inversion approach is very fast and covers all the needs of inversion of this type of data, from an almost instantaneous online/in‐field assessment of a set of measurements that offers a basis for making in‐field decisions, to an accurate inversion that produces final inversion models.

© 2025 European Association of Geoscientists & Engineers. © 2024 European Association of Geoscientists & Engineers.
Loading

Article metrics loading...

/content/journals/10.1002/nsg.12327
2025-01-21
2025-12-08

  • From This Site

    /content/journals/10.1002/nsg.12327
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Journal -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. Christensen, N.B. (1990) Optimized fast Hankel transform filters. Geophysical Prospecting, 38, 545‐568.
     [Google Scholar]
  2. Christensen, N.B., Reid, J.E. & Halkjær, M. (2009) Fast, laterally smooth inversion of airborne time‐domain electromagnetic data. Near Surface Geophysics, 7, 599‐612. https://doi.org/10.3997/1873‐0604.2009047.
     [Google Scholar]
  3. Christensen, N.B. (2016) Strictly horizontal lateral parameter correlation for 1D inverse modelling of large data sets. Near Surface Geophysics, 14, 391‐399. https://doi.org/10.3997/1873‐0604.2016028.
     [Google Scholar]
  4. Christensen, N.B. (2018) Interpretation attributes derived from AEM inversion models using the continuous wavelet transform. Near Surface Geophysics, 16, 665‐678. https://doi.org/10.1002/nsg.12018
     [Google Scholar]
  5. Christensen, N.B. (2021) Resolution attributes for AEM inversion models. A conceptual analysis and novel measures. Near Surface Geophysics, 20, 3–15. https://doi.org/10.1002/nsg.12188
     [Google Scholar]
  6. Christiansen, A.V., Pedersen, J.B., Auken, E., Soe, N.E., Holst, M.K. & Kristiansen, S.M. (2016) Improved geoarchaeological mapping with electromagnetic induction instruments from dedicated processing and inversion. Remote Sensing, 8(12), 1022. https://doi.org/10.3390/rs8121022
     [Google Scholar]
  7. Dabas, M., Anest, A., Thiesson, J. & Tabbagh, A. (2016) Slingram EMI devices for characterizing resistive features using apparent conductivity measurements: check of the DualEM‐421s instrument and field tests. Archaeological Prospection, 23, 165–180. https://doi.org/10.1002/arp.v23.3.
     [Google Scholar]
  8. Delefortrie, S., De Smedt, P., Saey, T., Van De Vijver, E. & Van Meirvenne, M. (2014) An efficient calibration procedure for correction of drift in EMI survey data. Journal of Applied Geophysics, 110, 115–125.
     [Google Scholar]
  9. El‐Qady, G., Metwaly, M., & Khozaym, A. (2014) Tracing buried pipelines using multi‐frequency electromagnetic: NRIAG. Journal of Astronomy and Geophysics, 3, 101–107. https://doi.org/10.1016/j.nrjag.2014.06.002.
     [Google Scholar]
  10. Guillemoteau, J. & Tronicke, J. (2015) Non‐standard ground conductivity meter configurations: evaluating sensitivities and applicability. Journal of Applied Geophysics, 118, 15‐23. https://doi.org/10.1016/j.jappgeo.2015.04.008.
     [Google Scholar]
  11. Guillemoteau, J. & Tronicke, J. (2016) Evaluation of a rapid hybrid spectral‐spatial domain 3D forward modeling approach for loop‐loop electromagnetic induction quadrature data acquired in low‐induction‐number environments. Geophysics, 81, E447–E458. https://doi.org/10.1190/geo2015‐0584.1.
     [Google Scholar]
  12. Guillemoteau, J., Christensen, N.B., Jacobsen, B.H. & Tronicke, J. (2017) Fast 3D multi‐channel deconvolution of electromagnetic induction loop‐loop apparent conductivity data sets acquired at low induction numbers. Geophysics, 82, E357‐E369.
     [Google Scholar]
  13. Johansen, H.K. & Sørensen, K. (1979) Fast Hankel transforms. Geophysical Prospecting, 27, 876‐901.
     [Google Scholar]
  14. von Hebel, C., Rudolph, S., Mester, A., Huisman, J., Kumbhar, P., Vereecken, H. & van der Kruk, J. (2014) Three‐dimensional imaging of subsurface structural patterns using quantitative large‐scale multiconfiguration electromagnetic induction data. Water Resources Research, 50, 2732–2748. https://doi.org/10.1002/2013WR014864.
     [Google Scholar]
  15. Kristiansen, S.M., Stott, D., Christiansen, A.V., Henriksen, P.S., Jessen, C., Mortensen, M.F., Pedersen, J.B., Sindbæk, S.M. & Ulriksen, J. (2022) Non‐destructive 3D prospection at the Viking Age fortress Borgring, Denmark. Journal of Archaeological Science Reports, 42, 103351. https://doi.org/10.1016/j.jasrep.2022.103351
     [Google Scholar]
  16. Maurer, H., Holliger, K. & Boerner, D.E. (1998). Stochastic regularization: Smoothness or similarity?Geophysical Research Letters, 25, 2889‐2892.
     [Google Scholar]
  17. Menke, W. (1989) Geophysical data analysis: Discrete inverse theory. New York: Academic Press.
     [Google Scholar]
  18. Møller, I., Jacobsen, B.H. & Christensen, N.B. (2001) Rapid inversion of 2‐D geoelectrical data by multichannel deconvolution. Geophysics, 66, 800‐808. https://doi.org/10.1190/1.1444969.
     [Google Scholar]
  19. Pedrera‐Parrilla, A., Van De Vijver, E., Van Meirvenne, M., Espejo‐ Pérez, A.J., Giráldez, J.V. & Vanderlinden, K. (2016) Apparent electrical conductivity measurements in an olive orchard under wet and dry soil conditions: significance for clay and soil water content mapping. Precision Agriculture, 17, 531‐545. https://doi.org/10.1007/s11119‐016‐9435‐z.
     [Google Scholar]
  20. Rezaei, M., Saey, T., Seuntjens, P., Joris, I., Boënne, W.VanMeirvenne, M. & Cornelis, W. (2016) Predicting saturated hydraulic conductivity in a sandy grassland using proximally sensed apparent electrical conductivity. Journal of Applied Geophysics, 126, 35‐41. https://doi.org/10.1016/j.jappgeo.2016.01.010.
     [Google Scholar]
  21. Rudolph, S., Wongleecharoen, C., Lark, R., Marchant, B., Garr, S.Herbst, M.Vereecken, H. & Weihermller, L. (2016) Soil apparent conductivity measurements for planning and analysis of agricultural experiments: a case story from Western‐Thailand. Geoderma, 267, 220‐229. https://doi.org/10.1016/j.geoderma.2015.12.013
     [Google Scholar]
  22. Serban, D.Z. & Jacobsen, B.H. (2001) The use of broadband prior covariance for inverse palaeoclimate estimation. Geophysical Journal International, 147, 29‐40.
     [Google Scholar]
  23. Simon, F.X., Sarris, A., Thiesson, J. & Tabbagh, A. (2015) Mapping of quadrature magnetic susceptibility/magnetic viscosity of soils by using multi‐frequency EMI. Journal of Applied Geophysics, 120, 36‐47. https://doi.org/10.1016/j.jappgeo.2015.06.007.
     [Google Scholar]
  24. Thomsen, P. (2023a) Near‐surface electromagnetic survey to support the design of urban development plans. In: Medhus, A.B., & Klinkby, L. (Eds.), Engineering geophysics, Boca Raton, FL: CRC Press, pp. 145–148.
     [Google Scholar]
  25. Thomsen, P. (2023b). Near‐surface electromagnetic survey to support the design of climate adaptation in urban development plans. In: Medhus, A.B., & Klinkby, L. (Eds.), Engineering geophysics. Boca Raton, FL: CRC Press, pp. 209–212.
     [Google Scholar]
  26. Tølbøll, R.J. & Christensen, N.B. (2007) The sensitivity functions of frequency‐domain magnetic dipole‐dipole systems. Geophysics, 72, F45–F56.
     [Google Scholar]
  27. Vereecken, H., Huisman, J.A., Hendricks Franssen, H.J., Brüggemann, N., Bogena, H. R., Kollet, S.Javaux, M., van der Kruk, J. & Vanderborght, J. (2015) Soil hydrology: recent methodological advances, challenges, and perspectives. Water Resources Research, 51, 2616‐2633. https://doi.org/10.1002/2014WR016852.
     [Google Scholar]
  28. Ward, S.H. & Hohmann, G.W. (1987) Electromagnetic theory for geophysical applications. In: Nabighian, M.N. (Ed.), Electromagnetic methods in applied geophysics Investigations in Geophysics 3. Houston, TX: Society of Exploration Geophysicists, pp. 131–311.
     [Google Scholar]
/content/journals/10.1002/nsg.12327
Loading
A fast hybrid 1D inversion approach for ground conductivity data
Near Surface Geophysics 23, 30 (2025); https://doi.org/10.1002/nsg.12327
/content/journals/10.1002/nsg.12327
/content/journals/10.1002/nsg.12327
Loading

Data & Media loading...

  • Article Type: Research Article
Keyword(s): frequency domain; ground conductivity meter data; inversion; modelling

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