1887

Abstract

Summary

Time-lapse resistivity surveys are used to monitor changes in the subsurface. In some situations, it is expected the resistivity will only decrease (or vice versa) with time. The 4-D ERT inversion technique includes a temporal smoothness constraint to ensure that the resistivity changes in a smooth manner with time. However, it does not directly constrain the direction of the temporal changes in the resistivity. In some cases, the time-lapse models might show an increase in the resistivity with time in parts of the inverse model where it is expected to only decrease based on other information. We modify the 4-D ERT inversion method to remove this artefact. We first use the standard 4-D ERT inversion algorithm to generate an initial model. If the resistivity is expected to decrease with time, for the model cells that show a resistivity increase a truncation procedure is used where the resistivities of the different time models are reset to the mean value. The method of transformations is then used to ensure that the resistivities of the later time models are always less than the first model. The constraints can be applied to selected regions in the model in cases where additional information is available.

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/content/papers/10.3997/2214-4609.201800427
2018-04-09
2024-03-29
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References

  1. AukenE., PellerinL., ChristensenN. B., SørensenK. I.
    , 2006, A survey of current trends in near-surface electrical and electromagnetic methods. Geophysics71, G249–G260
    [Google Scholar]
  2. BarkerR.D. and MooreJ.
    , 1998. The application of time-lapse electrical tomography in groundwater studies. The Leading Edge17, 1454–1458.
    [Google Scholar]
  3. ChambersJ.E., GunnD.A., WilkinsonP.B., MeldrumP.I., HaslamE., HolyoakeS., KirkhamM., KurasO., MerrittA. and WraggJ.
    2014. 4D electrical resistivity tomography monitoring of soil moisture dynamics in an operational railway embankment. Near Surface Geophysics12, 61–72.
    [Google Scholar]
  4. CassianiG., BrunoV., VillaA., FusiN. and BinleyA.M.
    2006. A saline trace test monitored via time-lapse surface electrical resistivity tomography. Journal of Applied Geophysics59, 244–259.
    [Google Scholar]
  5. DanielsR.W.
    1978. An introduction to numerical methods and optimization techniques. Elsevier North-Holland.
    [Google Scholar]
  6. deGroot-HedlinC. and ConstableS.
    1990. Occam’s inversion to generate smooth, two-dimensional models from magnetotelluric data. Geophysics55, 1613–1624.
    [Google Scholar]
  7. FarquharsonC.G. and OldenburgD.W.
    1998. Nonlinear inversion using general measures of data misfit and model structure. Geophysical Journal International134, 213–227.
    [Google Scholar]
  8. KimJ. H., YiM J., ParkS G. and KimJ.G.
    2009. 4-D inversion of DC resistivity monitoring data acquired over a dynamically changing earth model. Journal of Applied Geophysics68, 522–532.
    [Google Scholar]
  9. KurasO., WilkinsonP.B., MeldrumP.O., OxbyL.S., UhlemannS., Chambers, J.E., Binley, A., Graham, J., Smith, N.T. and de Atherton, N.
    , 2016. Geoelectrical monitoring of simulated subsurface leakage to support high-hazard nuclear decommissioning at the Sellafield Site, UK. Science of the Total Environment566–567, 350–359.
    [Google Scholar]
  10. LokeM.H., AcworthI. and DahlinT.
    2003. A comparison of smooth and blocky inversion methods in 2D electrical imaging surveys. Exploration Geophysics34, 182–187.
    [Google Scholar]
  11. LokeM.H., ChambersJ.E., RuckerD.F., KurasO. and WilkinsonP.B.
    2013. Recent developments in the direct-current geoelectrical imaging method. Journal of Applied Geophysics95, 135–156.
    [Google Scholar]
  12. LokeM.H., DahlinT. and RuckerD.F.
    2014. Smoothness-constrained time-lapse inversion of data from 3-D resistivity surveys. Near Surface Geophysics12, 5–24.
    [Google Scholar]
  13. LokeM.H., WilkinsonP.B., ChambersJ. E. and MeldrumP.I.
    , 2017. Rapid inversion of data from 2-D resistivity surveys with electrodes displacements. Geophysical Prospecting (in press) doi: 10.1111/1365-2478.12522.
    [Google Scholar]
  14. RosqvistH., LerouxV., DahlinT., JohanssonS. and SvenssonM.
    2010. An evaluation of the potential of the geoelectrical resistivity method for mapping gas migration in landfills. SAGEEP 2010 Proceedings (Volume 1), Keystone, Colorado, 369–378.
    [Google Scholar]
  15. RosqvistH., LerouxV., DahlinT., SvenssonM., LindsjoM, ManssonC-H. and JohanssonS.
    , 2011. Mapping landfill gas migration using resistivity monitoring. Waste and Resource Management, 164 (WR1), 3–15.
    [Google Scholar]
  16. Rucker, D.F, Crook, N., Winterton, J., McNeill, M., Baldyga, C.A., Noonan, G. and Fink, J.B.
    2014. Real-time electrical monitoring of reagent delivery during a subsurface amendment experiment. Near Surface Geophysics12, 151–163.
    [Google Scholar]
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