1887
  1. Home
  2. A-Z Publications
  3. Near Surface Geophysics
  4. Volume 9, Issue 5
  5. Article
Volume 9 Number 5
  • ISSN: 1569-4445
  • E-ISSN: 1873-0604

Abstract

ABSTRACT

The precision of ground‐penetrating radar velocity models is seldom reported, despite their common use for quantifying subsurface properties. We explore influences on the resolution of ground‐penetrating radar velocity analysis and demonstrate a Monte Carlo method for obtaining the implied precision in velocity estimates. A series of synthetic common‐midpoint gathers, which assume Ricker wavelets of 50 MHz, 100 MHz and 200 MHz frequencies as source pulses, simulate hyperbolic reflections from the bases of three horizontal layers, each with interval velocity and thickness of 0.1 m/ns and 2 m, respectively. With these, we use coherence analysis to show that the principal influence on stacking velocity resolution is the traveltime moveout, normalized by the wavelet period, exhibited across some offset range. Where moveout exceeds the period by factors of, e.g., 3 and 6, is resolved to [–6.5, +8.2]% to [–3.6, +4.0]%, respectively, at the 50% coherence threshold. The temporal duration of coherence responses is expressed as a one‐quarter wavelet period either side of the stacking traveltime. Coherence resolutions are used in Monte Carlo simulations to derive the implied precision in the interval stacking velocity and its derivative properties. These analyses are repeated for field common‐midpoint data, acquired using 50 MHz antennas, on Quaternary glacio‐fluvial media overlying a Cambrian basement (<15 m deep). For three reflections identified in these data, the velocity and temporal resolution of coherence responses vary in a quantitatively similar way to events in the synthetic data. For the corresponding layers, Monte Carlo simulations yield precision estimates for , layer thickness and fractional water content. The procedure predicts a reasonable model of water content decreasing with depth, in accordance with increasing pore compaction and provides a robust error analysis; the uncertainty in estimates of the fractional water content of two (assumed) water‐saturated layers is ±2.6% and ±2.1% (shallower and deeper, respectively). Monte Carlo simulations are recommended as an efficient means of establishing the precision in quantitative estimates of subsurface properties derived from ground‐penetrating radar velocities, particularly where ground‐truth data are unavailable.

© European Association of Geoscientists and Engineers © 2011 European Association of Geoscientists and Engineers
Loading

Article metrics loading...

/content/journals/10.3997/1873-0604.2011019
2018-12-18
2024-04-24

  • From This Site

    /content/journals/10.3997/1873-0604.2011019
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Journal -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. AlkhalifahT.1997. Velocity analyses using nonhyperbolic moveout in transversely isotropic media. Geophysics62, 1839–1854.
     [Google Scholar]
  2. AllenP.M. and JacksonA.A.1988. Geology of the country around Harlech: Memoirs of the British Geological Survey.HMSO.
     [Google Scholar]
  3. AnnanA.P.2005. Ground‐penetrating radar. In: Near Surface Geophysics (ed. D.K.Butler ), pp. 357–438. SEG.
     [Google Scholar]
  4. BarnesA.E.1992. Another look at NMO stretch. Geophysics57, 749–751.
     [Google Scholar]
  5. BechtA., AppelE. and DietrichP.2006. Analysis of multi‐offset GPR data: A case study in a coarse‐grained gravel aquifer. Near Surface Geophysics4, 227–240.
     [Google Scholar]
  6. BerardB. and MaillolJ.‐C.2008. Common‐ and multi‐offset ground‐penetrating radar study of a Roman villa, Tourega, Portugal. Archaeological Prospection15, 32–46.
     [Google Scholar]
  7. BoothA.D., ClarkR.A., HamiltonK. and MurrayT.2010a. Multi‐offset ground penetrating radar methods to image buried foundations of a town wall, Great Yarmouth, UK. Archaeological Prospection17, 103–116. doi:10.1002/arp.377
     [Google Scholar]
  8. BoothA.D., ClarkR.A. and MurrayT.2010b. Semblance response to a ground‐penetrating radar wavelet and resulting errors in velocity analysis. Near Surface Geophysics8, 235–246.
     [Google Scholar]
  9. BoothA.D., LinfordN.T., ClarkR.A. and MurrayT.2008. Three‐dimensional, multi‐offset GPR imaging of archaeological targets. Archaeological Prospection15, 1–20.
     [Google Scholar]
  10. BradfordJ.H. and HarperJ.T.2005. Wavefield migration as a tool for estimating spatially continuous radar velocity and water content in glaciers. Geophysical Research Letters32, L08502.
     [Google Scholar]
  11. BradfordJ.H., NicholsJ., MikesellT.D. and HarperJ.T.2009. Continuous profiles of electromagnetic wave velocity and water content in glaciers: An example from Bench Glacier, Alaska, USA. Annals of Glaciology50, 1–9.
     [Google Scholar]
  12. BradfordJ.H. and SawyerD.S.2002. Depth characterization of shallow aquifers with seismic reflection, Part II – Prestack depth migration and field examples. Geophysics67, 98–109.
     [Google Scholar]
  13. CastleR.J.1994. A theory of normal moveout. Geophysics59, 983–999.
     [Google Scholar]
  14. DeregowskiS.M.1986. What is DMO?First Break4, 7–24.
     [Google Scholar]
  15. DixC.H.1955. Seismic velocities from surface measurements. Geophysics20, 68–86.
     [Google Scholar]
  16. EndresA.L., MurrayT., BoothA.D. and WestL.J.2009. A new framework for estimating englacial water content and pore geometry using combined radar and seismic wave velocities. Geophysical Research Letters36, L04501.
     [Google Scholar]
  17. GreavesR.J., LesmesD.P., LeeJ.M., and ToksözM.N.1996. Velocity variations and water content estimated from multi‐offset, ground‐penetrating radar. Geophysics61, 683–695.
     [Google Scholar]
  18. GusmeroliA., MurrayT., JanssonP., PetterssonR., AschwandenA. and BoothA.D.2010. Vertical distribution of water within the polythermal Storglaciären. Journal of Geophysical Research115, F04002.
     [Google Scholar]
  19. HaleD.1984. Dip‐moveout by Fourier transform. Geophysics49, 741–757.
     [Google Scholar]
  20. HattonL., WorthingtonM.H. and MakinJ.1986. Seismic Data Processing,2nd edn. Blackwell Scientific Publications.
     [Google Scholar]
  21. HuismanJ.A., HubbardS.S., RedmanJ.D. and AnnanA.P.2003. Measuring soil water content with ground penetrating radar: A review. Vadose Zone Journal2, 476–491.
     [Google Scholar]
  22. JacobR.W. and HermanceJ.F.2004. Assessing the precision of GPR velocity and vertical two‐way travel time estimates. Journal of Environmental and Engineering Geophysics9, 143–153.
     [Google Scholar]
  23. JacobR.W. and HermanceJ.F.2005. Random and non‐random uncertainties in precision GPR measurements: Identifying and compensating for instrumental drift. Subsurface Sensing Technologies and Applications6, 59–71.
     [Google Scholar]
  24. JacobR.W., HermanceJ.F. and van der KrukJ.2010. GPR reflection and dispersion analysis methods for water content: Multi‐year study of GPR estimates and soil core measurements of water content.13th International Conference on Ground Penetrating Radar, Lecce, Italy, 21–25 June 2010, Expanded Abstracts.
     [Google Scholar]
  25. JonesI.F.2010. An Introduction to Velocity Model Building.EAGE.
     [Google Scholar]
  26. KhalilM.A., HafezM.A., Monteiro SantosF., RamalhoE.C., MesbahH.S.A. and El‐QadyG.M.2010. An approach to estimate porosity and groundwater salinity by combined application of GPR and VES: A case study in the Nubian sandstone aquifer. Near Surface Geophysics8, 223–233.
     [Google Scholar]
  27. LevinF.K.1971. Apparent velocity from dipping interface reflections. Geophysics36, 510–516.
     [Google Scholar]
  28. LooyengaM.1965. Dielectric constants of heterogeneous mixture. Physica31, 401–406.
     [Google Scholar]
  29. MacheretY.Y. and GlazovskyA.F.2000. Estimation of absolute water content in Spitsbergen glaciers from radar sounding data. Polar Research19, 205–216.
     [Google Scholar]
  30. MewesA., KulessaB., McKinleyJ.D. and BinleyA.M.2010. Anisotropic seismic inversion using a multigrid Monte Carlo approach. Geophysical Journal International183, 267–276. doi:10.1111/j.1365‐246X.2010.04707.x
     [Google Scholar]
  31. MoyseyS.2007. The role of uncertainty and scale in rock physics transforms on sequential and integrated data fusion methods. Proceedings of the 2007 Joint Assembly of the AGU, Acapulco, Mexico, 22–25 May, Expanded Abstracts.
     [Google Scholar]
  32. MoyseyS. and KnightR.J.2004. Modeling the field‐scale relationship between dielectric constant and water content in heterogeneous systems. Water Resources Research40, W03510. doi:10.1029/2003WR002589
     [Google Scholar]
  33. MoyseyS., SinghaK. and KnightR.2005. A framework for inferring field‐scale rock physics relationships through numerical simulation. Geophysical Research Letters32, L08304. doi:10.1029/2004GL022152
     [Google Scholar]
  34. MurrayT., BoothA.D. and RippinD.M.2007. Water‐content of glacier ice: Limitations on estimated from velocity analysis of surface ground‐penetrating radar surveys. Journal of Environmental and Engineering Geophysics12, 87–99.
     [Google Scholar]
  35. MurrayT., StuartG.W., FryM., GambleN.H. and CrabtreeM.D.2000. Englacial water distribution in a temperate glacier from surface and borehole radar velocity analysis. Journal of Glaciology46, 389–397.
     [Google Scholar]
  36. NeidellN.S. and TanerM.T.1971. Semblance and other coherency measures for multichannel data. Geophysics36, 482–497.
     [Google Scholar]
  37. ParenJ.G.1970. Dielectric properties of ice. PhD thesis, University of Cambridge.
  38. PipanM., BaradelloL., ForteE., PrizzonA. and FinettiI.1999. 2‐D and 3‐D processing and interpretation of multi‐fold ground‐penetrating radar data: A case history from an archaeological site. Journal of Applied Geophysics41, 271–292.
     [Google Scholar]
  39. RadzeviciusS., ChenC.‐C., PetersJr.L. and DanielsJ.J.2003. Near‐field radiation dynamics through FDTD modelling. Journal of Applied Geophysics52, 75–91.
     [Google Scholar]
  40. ReynoldsJ.M.2000. An Introduction to Applied and Environmental Geophysics,2nd edn. Wiley.
     [Google Scholar]
  41. RothmanD.H.1986. Automatic estimation of large residual statics corrections. Geophysics51, 332–346.
     [Google Scholar]
  42. SchmalholzJ., StoffregenH., KemnaA. and YaramanciU.2004. Imaging of water content distributions inside a lysimeter using GPR tomography. Vadose Zone Journal3, 1106–1115.
     [Google Scholar]
  43. SchneiderW.A.1971. Developments in seismic data processing and analysis (1968–1970). Geophysics36, 1043–1073.
     [Google Scholar]
  44. SheriffR.E. and GeldartL.P.1999. Exploration Seismology,2nd edn. Cambridge University Press.
     [Google Scholar]
  45. SinisaloA, GrinstedA., MooreJ.C., KärkäsE and PetterssonR.2003. Snow‐accumulation studies in Antarctica with ground‐penetrating radar using 50, 100 and 800 MHz antenna frequencies. Annals of Glaciology37, 194–198.
     [Google Scholar]
  46. SteelmanC.M. and EndresA.L.2009. Evolution of high‐frequency ground‐penetrating radar direct wave propagation during thin frozen soil layer development. Cold Regions Science and Technology57, 116–122.
     [Google Scholar]
  47. TanerM.T. and KoehlerF.1969. Velocity spectra – Digital computer derivation and applications of velocity functions. Geophysics34, 859–881.
     [Google Scholar]
  48. ToppG.C., DavisJ.L. and AnnanA.P.1980. Electromagnetic determination of soil water content: Measurements in coaxial transmission lines. Water Resources Research24, 945–952.
     [Google Scholar]
  49. TronickeJ., DietrichP. and AppelE.2000. Georadar velocity determination: A comparison of different techniques.Proceedings of the 6th Meeting of the EEGS‐ES, Bochum, Germany, Expanded Abstracts.
     [Google Scholar]
  50. TuressonA.2006. Water content and porosity estimates from ground‐penetrating radar and resistivity. Journal of Applied Geophysics58, 99–111.
     [Google Scholar]
  51. Van OvermeerenR.A., SariowanS.V. and GehrelsJ.C.1997. Ground penetrating radar for determining volumetric soil water content; Results of comparative measurements at two test sites. Journal of Hydrology197, 316–338.
     [Google Scholar]
  52. WeihermüllerL., HuismanJ.A., LambotS., HerbstM. and VereeckenH.2007. Mapping the spatial variation of soil water content at the field scale with different ground penetrating radar techniques. Journal of Hydrology340, 205–216.
     [Google Scholar]
  53. YanJ. and TsvankinI.2008. AVO‐sensitive semblance analysis for wide‐azimuth data. Geophysics73, U1–U11.
     [Google Scholar]
  54. YilmazO.2001. Seismic Data Analysis: Processing, Inversion and Interpretation of Seismic Data.SEG.
     [Google Scholar]
  55. YilmazO. and ClaerboutJ.F.1980. Prestack partial migration. Geophysics45, 1753–1779.
     [Google Scholar]
http://instance.metastore.ingenta.com/content/journals/10.3997/1873-0604.2011019
Loading
Influences on the resolution of GPR velocity analyses and a Monte Carlo simulation for establishing velocity precision
Near Surface Geophysics 9, 399 (2011); https://doi.org/10.3997/1873-0604.2011019
/content/journals/10.3997/1873-0604.2011019
/content/journals/10.3997/1873-0604.2011019
Loading

Data & Media loading...

  • Article Type: Research Article

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