1887
Volume 67, Issue 8
  • E-ISSN: 1365-2478

Abstract

ABSTRACT

Electromagnetic geophysical methods often rely on measurements of naturally occurring or artificially impressed electric fields. It is technically impossible, however, to measure the electric field directly. Instead, the electric field is approximated by recording the voltage difference between two electrodes and dividing the obtained voltage by the distance between the electrodes. Typically, modelling and inversion algorithms assume that the electric fields are obtained over infinitely short and thus measured fields are assigned to a single point between the electrodes. Such procedures imply several assumptions: (1) The electric field between the two electrodes is regarded as constant or being a potential field and (2) the receiver dimensions are negligible compared to the dimensions of the underlying modelling grid. While these conditions are often fulfilled for horizontal electric fields, borehole sensors for recordings of the vertical electric field have dimensions in the order of ≈100 m and span several modelling grid cells. Observations from such elongated borehole sensors can therefore only be interpreted properly if true receiver dimensions and variations of electrical conductivity along the receiver are considered. Here, we introduce a numerical solution to include the true receiver geometry into electromagnetic modelling schemes, which does not rely on such simplifying assumptions. The algorithm is flexible, independent of the chosen numerical method to solve Maxwell's equations and can easily be implemented in other electromagnetic modelling and inversion codes. We present conceptual modelling results for land‐based controlled source electromagnetic scenarios and discuss consideration of true receiver geometries for a series of examples of horizontal and vertical electric field measurements. Comparison with Ez data measured in an observation borehole in a producing oil field shows the importance of both considering the true length of the receiver and also its orientation. We show that misalignment from the vertical axis as small as 0.1° may seriously distort the measured signal, as horizontal electric field components are mapped into the desired vertical component. Adequate inclusion of elongated receivers in modelling and inversion can also help reducing effects of static shift when interpreting (natural source) magnetotelluric data.

Loading

Article metrics loading...

/content/journals/10.1111/1365-2478.12830
2019-07-12
2020-04-07
Loading full text...

Full text loading...

References

  1. ChaveA.D. and CoxC.S.1982. Controlled electromagnetic sources for measuring electrical conductivity beneath the oceans 1. Forward problem and model study. Journal of Geophysical Research87, 5327–5338.
    [Google Scholar]
  2. ChaveA.D. and SmithJ.T.1994. On electric and magnetic galvanic distortion tensor decompositions. Journal of Geophysical Research99, 4669–4682.
    [Google Scholar]
  3. ChaveA.D., ThomsonD.J. and AnderM.E.1987. On the robust estimation of power spectra, coherences, and transfer functions. Journal of Geophysical Research: Solid Earth92, 633–648.
    [Google Scholar]
  4. EgbertG.D. and BookerJ.R.1986. Robust estimation of geomagnatic transfer functions. Geophysical Journal of the Royal Astronomical Society87, 173–194.
    [Google Scholar]
  5. GrayverA.V., StreichR. and RitterO.2013. Three‐dimensional parallel distributed inversion of CSEM data using a direct forward solver. Geophysical Journal International193, 1432–1446.
    [Google Scholar]
  6. JiracekG.R.1990. Near‐surface and topographic distortions in electromagentic induction. Surveys in Geophysics11, 163–203.
    [Google Scholar]
  7. JonesA.G.1988. Static shift of magnetotelluric data and its removal in sedimentary basin environment. Geophysics55, 967–978.
    [Google Scholar]
  8. KalscheuerT., BlakeS., PodgorskiJ.E., WagnerF., GreenA.G., MaurerH., et al. 2015. Joint inversions of three types of electromagnetic data explicitly constrained by seismic observations: results from the central Okavango Delta, Botswana. Geophysical Journal International202, 1429–1452.
    [Google Scholar]
  9. KalscheuerT., DossowL., JuhojunttiN. and DynesiusL.2018a. Surface and borehole magnetotelluric measurements to delineate an ore deposit in northern Sweden. Presented at the 2nd Conference on Geophysics for Mineral Exploration and Mining. EAGE Publications BV.
  10. KalscheuerT., HübertJ., KuvshinovA., LochbuhlerT. and PedersenL.B.2012. A hybrid regularization scheme for the inversion of magnetotelluric data from natural and controlled sources to layer and distortion parameters. Geophysics77, E301–E315.
    [Google Scholar]
  11. KalscheuerT., JuhojunttiN. and VaittinenK.2018b. Two‐dimensional magnetotelluric modelling of ore deposits: improvements in model constraints by inclusion of borehole measurements. Surveys in Geophysics39, 467–507.
    [Google Scholar]
  12. MiensopustM.P.2017. Application of 3‐d electromagnetic inversion in practice: challenges, pitfalls and solution approaches. Surveys in Geophysics38, 869–933.
    [Google Scholar]
  13. NewmanG.A. and BoggsP.T.2004. Solution accelerators for large‐scale three‐dimensional electromagnetic inverse problems. Inverse Problems20. https://doi.org/10.1088/0266-5611/20/6/S10
    [Google Scholar]
  14. PollH.E., WeaverJ.T. and JonesA.G.1989. Calculations of voltages for magnetotelluric modelling of a region with near‐surface inhomogenities. Physics of the Earth and Planetary Interiors53, 287–297.
    [Google Scholar]
  15. SchallerA., HunzikerJ., DrijkoningenG. and StreichR.2014. Sensitivity of the near‐surface vertical electric field in land controlled‐source electromagnetic monitoring. SEG Technical Program Expanded Abstracts 2014, 838–843.
  16. SimpsonF. and BahrK.2005. Practical Magnetotellurics. Cambridge University Press.
    [Google Scholar]
  17. SoyerW., MiorelliF. and MackieR.L.2018. Considering true layout geometry in magnetotelluric modeling. Paper presented at the Abstract, 24th EM Induction Workshop, Helsingør, Denmark, August 12‐19.
  18. StreichR.2009. 3d finite‐difference frequency‐domain modeling of controlled‐source electromagnetic data: direct solution and optimzation for high accuracy. Geophysics74, 95–105.
    [Google Scholar]
  19. StreichR. and BeckenM.2011. Electromagnetic fields generated by finite‐length wire source: comparison with point‐dipole solutions. Geophysical Prospecting59, 361–374.
    [Google Scholar]
  20. StreichR., BeckenM. and RitterO.2013. Robust processing of noisy land‐based controlled source electromagnetic data. Geophysics78, 237–247.
    [Google Scholar]
  21. TietzeK., RitterO., PatzerC., VeekenP. and DillenM.2019. Repeatability of land‐based controlled‐source electromagnetic measurements in industrialised areas and including vertical electric fields. Geophysical Journal International218, 1552–1571.
    [Google Scholar]
  22. TietzeK., RitterO. and VeekenP.2015. Controlled‐source electromagnetic monitoring of reservoir oil saturation using a novel borehole‐to‐surface configuration. Geophysical Prospecting63, 1468–1490.
    [Google Scholar]
  23. WiriantoM., MulderW.A. and SlobE.C.2010. A feasibility study of land CSEM reservoir monitoring in a complex 3d‐model. Geophysical Journal International181, 741–755.
    [Google Scholar]
  24. ZhdanovM.S.2010. Electromagnetic geophysics: notes from the past and the road ahead. Geophysics75, 75A49–75A66.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journals/10.1111/1365-2478.12830
Loading
/content/journals/10.1111/1365-2478.12830
Loading

Data & Media loading...

  • Article Type: Research Article
Keyword(s): Computing aspects , Electromagnetics , Inversion , Modelling and Numerical study
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