1887
Volume 66, Issue 3
  • E-ISSN: 1365-2478

Abstract

ABSTRACT

Resistivity monitoring surveys are used to detect temporal changes in the subsurface using repeated measurements over the same site. The positions of the electrodes are typically measured at the start of the survey program and possibly at occasional later times. In areas with unstable ground, such as landslide‐prone slopes, the positions of the electrodes can be displaced by ground movements. If this occurs at times when the positions of the electrodes are not directly measured, they have to be estimated. This can be done by interpolation or, as in recent developments, from the resistivity data using new inverse methods. The smoothness‐constrained least squares optimisation method can be modified to include the electrode positions as additional unknown parameters. The Jacobian matrices with the sensitivity of the apparent resistivity measurements to changes in the electrode positions are then required by the optimisation method. In this paper, a fast adjoint‐equation method is used to calculate the Jacobian matrices required by the least squares method to reduce the calculation time. In areas with large near‐surface resistivity contrasts, the inversion routine sometimes cannot accurately distinguish between electrode displacements and subsurface resistivity variations. To overcome this problem, the model for the initial time‐lapse dataset (with accurately known electrode positions) is used as the starting model for the inversion of the later‐time dataset. This greatly improves the accuracy of the estimated electrode positions compared to the use of a homogeneous half‐space starting model. In areas where the movement of the electrodes is expected to occur in a fixed direction, the method of transformations can be used to include this information as an additional constraint in the optimisation routine.

Loading

Article metrics loading...

/content/journals/10.1111/1365-2478.12522
2017-05-15
2024-04-23
Loading full text...

Full text loading...

References

  1. AukenE., PellerinL., ChristensenN.B. and SørensenK.I.2006. A survey of current trends in near‐surface electrical and electromagnetic methods. Geophysics71, G249–G260.
    [Google Scholar]
  2. BingZ. and GreenhalghS.A.1999. Explicit expressions and numerical calculations for the Fréchet and second derivatives in 2.5D Helmholtz equation inversion. Geophysical Prospecting47, 443–468.
    [Google Scholar]
  3. ChambersJ.E., WilkinsonP.B., KurasO., FordJ.R., GunnD.A., MeldrumP.I.et al. 2011. Three‐dimensional geophysical anatomy of an active landslide in Lias Group mudrocks, Cleveland Basin, UK. Geomorphology125, 472–484.
    [Google Scholar]
  4. ChambersJ.E., GunnD.A., WilkinsonP.B., MeldrumP.I., HaslamE., HolyoakeS.et al. 2014. 4D electrical resistivity tomography monitoring of soil moisture dynamics in an operational railway embankment. Near Surface Geophysics12, 61–72.
    [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. DeyA. and MorrisonH.F.1979. Resistivity modelling for arbitrary shaped two‐dimensional structures. Geophysical Prospecting27, 106–136.
    [Google Scholar]
  8. FarquharsonC.G. and OldenburgD.W.1998. Nonlinear inversion using general measures of data misfit and model structure. Geophysical Journal International134, 213–227.
    [Google Scholar]
  9. FarquharsonC.G. and OldenburgD.W.2004. A comparison of automatic techniques for estimating the regularization parameter in non‐linear inverse problems. Geophysical Journal International156, 411–425.
    [Google Scholar]
  10. GolubG. and van LoanC.F.1996. Matrix Computations, 3rd edn. The John Hopkins University Press.
    [Google Scholar]
  11. GunnD.A., ChambersJ.E., HobbsP.R.N., FordJ.R., WilkinsonP.B., JenkinsG.O.et al. 2013. Rapid observations to guide the design of systems for long‐term monitoring of a complex landslide in the Upper Lias clays of North Yorkshire, UK. Quarterly Journal of Engineering Geology and Hydrogeology46, 323–336.
    [Google Scholar]
  12. JenningsA. and McKeownJ.J.1992. Matrix Computation, 2nd edn. John Wiley and Sons Ltd.
    [Google Scholar]
  13. KimJ.H.2014. Simultaneous inversion of resistivity structure and electrode locations in ERT. 20th European Meeting of Environmental and Engineering Geophysics, Athens, Greece, September 14–18, 2014.
  14. LiY. and OldenburgD.W.2000. 3‐D inversion of induced polarization data. Geophysics65, 1931–1945.
    [Google Scholar]
  15. LokeM.H. and BarkerR.D.1996. Rapid least‐squares inversion of apparent resistivity pseudosections by a quasi‐Newton method. Geophysical Prospecting44, 131–152.
    [Google Scholar]
  16. LokeM.H.2000. Topographic modelling in resistivity imaging inversion. 62nd EAGE Conference & Technical Exhibition, Glasgow, Scotland, Extended Abstracts, D‐2.
  17. 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]
  18. LokeM.H. and DahlinT.2010. Methods to reduce banding effects in 3‐D resistivity inversion. 16th European Meeting of Environmental and Engineering Geophysics, Zurich, Switzerland, Expanded Abstracts, A16.
  19. 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]
  20. 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]
  21. LokeM.H., WilkinsonP.B. and ChambersJ.E.2016. 3‐D resistivity inversion with electrodes displacements. ASEG‐PESA‐AIG 25th Geophysical Conference and Exhibition, August 21–24, 2016, Adelaide, Australia, Extended Abstracts, 809–813.
  22. McGillivrayP.R. and OldenburgD.W.1990. Methods for calculating Fréchet derivatives and sensitivities for the non‐linear inverse problem: a comparative study. Geophysical Prospecting38, 499–524.
    [Google Scholar]
  23. MerrittA.J., ChambersJ.E., MurphyW., WilkinsonP.B., WestL.J., GunnD.A.et al. 2014. 3D ground model development for an active landslide in Lias mudrocks using geophysical, remote sensing and geotechnical methods. Landslides11, 537–550.
    [Google Scholar]
  24. OldenburgD.W. and LiY.1994. Inversion of induced polarization data. Geophysics59, 1327–1341.
    [Google Scholar]
  25. PressW.H., TeukolskyS.A., VetterlingW.T. and FlanneryB.P.1992. Numerical Recipes in C, 2nd edn. Cambridge University Press.
    [Google Scholar]
  26. QueraltP., PousJ. and MarcuelloA.1991. 2‐D resistivity modeling: an approach to arrays parallel to the strike direction. Geophysics56, 941–950.
    [Google Scholar]
  27. SasakiY.1989. Two‐dimensional joint inversion of magnetotelluric and dipole‐dipole resistivity data. Geophysics54, 254–262.
    [Google Scholar]
  28. SasakiY.1994. 3‐D resistivity inversion using the finite element method. Geophysics59, 1839–1848.
    [Google Scholar]
  29. SchwarzH.R., RutishauserH. and StiefelE.1973. Numerical Analysis of Symmetric Matrices. Prentice‐Hall, Inc.
    [Google Scholar]
  30. SeatonW.J. and BurbeyT.J.2000. Aquifer characterization in the Blue Ridge physiographic province using resistivity profiling and borehole geophysics: geologic analysis. Journal of Environmental & Engineering Geophysics5(3), 45–58.
    [Google Scholar]
  31. SilvesterP.P. and FerrariR.L.1990. Finite Elements for Electrical Engineers, 2nd edn. Cambridge University Press.
    [Google Scholar]
  32. SupperR., OttowitzD., JochumB., RömerA., PfeilerS., KauerS.et al. 2014a. Geoelectrical monitoring of frozen ground and permafrost in alpine areas: field studies and considerations towards an improved measuring technology. Near Surface Geophysics12, 93–115.
    [Google Scholar]
  33. SupperR., OttowitzD., JochumB., KimJ.H., RömerA., BaronI.et al. 2014b. Geoelectrical monitoring: an innovative method to supplement landslide surveillance and early warning. Near Surface Geophysics12, 133–150.
    [Google Scholar]
  34. UhlemannS., WilkinsonP.B., ChambersJ.E., MaurerH., MerrittA.J., GunnD.A.et al. 2015a. Interpolation of landslide movements to improve the accuracy of 4D geoelectrical monitoring. Journal of Applied Geophysics121, 93–105.
    [Google Scholar]
  35. UhlemannS., SmithA., ChambersJ.E., DixonN., DijkstraT., HaslamE.et al. 2015b. Assessment of ground‐based monitoring techniques applied to landslide investigations. Geomorphology253, 438–451.
    [Google Scholar]
  36. WilkinsonP.B., ChambersJ.E., MeldrumP.I., GunnD.A., OgilvyR.D. and KurasO.2010. Predicting the movements of permanently installed electrodes on an active landslide using time‐lapse geoelectrical resistivity data only. Geophysical Journal International183, 543–556.
    [Google Scholar]
  37. WilkinsonP.B., UhlemannS., ChambersJ.C., MeldrumP.I. and LokeM.H.2015a. Development and testing of displacement inversion to track electrode movements on 3D Electrical Resistivity Tomography monitoring grids. Geophysical Journal International200, 1566–1581.
    [Google Scholar]
  38. WilkinsonP.B., UhlemannS., MeldrumP.I., ChambersJ.C., CarrièreS., OxbyL.S.et al. 2015b. Adaptive time‐lapse optimized survey design for electrical resistivity tomography monitoring. Geophysical Journal International203, 755–766.
    [Google Scholar]
  39. WilkinsonP.B., ChambersJ.E., UhlemannS., MeldrumP.I., SmithA., DixonN.et al. 2016. Reconstruction of landslide movements by inversion of 4‐D electrical resistivity tomography monitoring data. Geophysical Research Letters43, 1166–1174.
    [Google Scholar]
  40. XuS.Z., DuanB.C. and ZhangD.H.2000. Selection of the wavenumbers k using an optimization method for the inverse Fourier transform in 2.5‐D electrical modeling. Geophysical Prospecting48, 789–796.
    [Google Scholar]
  41. ZhouB. and DahlinT.2003. Properties and effects of measurement errors on 2D resistivity imaging surveying. Near Surface Geophysics1, 105–117.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journals/10.1111/1365-2478.12522
Loading
/content/journals/10.1111/1365-2478.12522
Loading

Data & Media loading...

  • Article Type: Research Article
Keyword(s): Imaging; Inversion; Monitoring; Resistivity; Time lapse

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