Advertisement

Characterizing Uncertainties in the Geophysical Properties of Soils in the El Paso, Texas Region

  • Diane I. DoserEmail author
  • Mark R. Baker
Chapter
  • 30 Downloads
Part of the Studies in Computational Intelligence book series (SCI, volume 835)

Abstract

Developing reliable methods to estimate the uncertainties in the geophysical properties of materials has wide applications across the field of geophysics. Uncertainty estimates aid in helping to devise geophysical sampling schemes, applying inversion techniques to geophysical data and to assess how operator expertise, instrumentation or other factors influence survey accuracy. In this study we evaluate closely spaced geophysical data collected from magnetic, conductivity and gravity surveys over a range of soils deposited in the river valley of the Rio Grande. Our results indicate strong relations between agricultural soil classification and geophysical property variability. They also suggest that power-law processes are of limited usefulness in explaining variability. In addition we found no useful bivariate correlations that would allow us to use a rapid, dense measurement as a proxy for more difficult surveys.

Notes

Acknowledgements

A. Woody, B. Eslick, J. Olgin and A. Wamalwa assisted in the collection of gravity data for this study. The fall 2008 semester “Exploration Geophysics—Non-seismic Methods” class assisted in collection of the conductivity and magnetics data for the well field. C. Montana collected the magnetics data for the alfalfa field. We thank V. Kreinovich for the many fruitful conversations he has had with us regarding estimating uncertainties in geophysical data sets and meaningful ways to analyze the data.

References

  1. 1.
    B.N. Arunshankar, Use of earth resistivity method for monitoring saline groundwater movement in aquifers. Thesis, University of Texas at El Paso (1993)Google Scholar
  2. 2.
    G. Chen, Q. Cheng, H. Zhang, Matched filtering method for separating magnetic anomaly using fractal model. Comput. Geosci. 90, 179–188 (2016)CrossRefGoogle Scholar
  3. 3.
    A. Clauset, C.R. Shalizi, M.E.J. Newman, Power-law distributions in empirical data. SIAM Rev. 51(4), 661–703 (2009)MathSciNetCrossRefGoogle Scholar
  4. 4.
    D.I. Doser, M.R. Baker, B.E. Eslick et al., The noise/data conundrum in gravity and magnetic surveys of fluvial sediments, near the Rio Grande, west Texas, in Abstract of the Fall Meeting, American Geophysical Union, Abstract IN51C-1168 (2008)Google Scholar
  5. 5.
    D. Doser, M. Baker, R. Langford et al., Agricultural soil maps as a framework for conducting shallow subsurface investigations in the Rio Grande valley near El Paso, in Proceedings, Symposium on the Application of Geophysics to Engineering and Environmental Problems (SAGEEP), Denver, CO (2007), pp. 582–589Google Scholar
  6. 6.
    M.E. Gettings, Multifractal model of magnetic susceptibility distributions in some igneous rocks. Nonlinear Proc. Geophys. 19, 635–642 (2012)CrossRefGoogle Scholar
  7. 7.
    P. Michaelsen, R.A. Henderson, P.J. Crosdale et al., Facies architecture and depositional dynamics of the Upper Permian Rangal coal measures Bowen Basin, Australia. J. Sediment Res. 70(4), 879–895 (2000)CrossRefGoogle Scholar
  8. 8.
    Natural Resources Conservation Service, Web Soil Survey (2016), https://websoilsurvey.sc.egov.usda.gov/App/WebSoilSurvey.aspx. Accessed 17 June 2017
  9. 9.
    M. Pilkington, J.P. Todoeschuck, Fractal magnetization of continental crust. Geophys. Res. Lett. 20, 627–630 (1993)CrossRefGoogle Scholar
  10. 10.
    A. Salem et al., Depth to Curie temperature across the central Red Sea from magnetic data using the de-fractal method. Tectonophysics 624, 75–86 (2014)CrossRefGoogle Scholar
  11. 11.
    B. Sellepack, The stratigraphy of the Pliocene-Pleistocene Santa Fe Group in the southern Mesilla Basin. Thesis, University of Texas at El Paso (2003)Google Scholar
  12. 12.
    D.L. Turcotte, Fractals and Chaos in Geology and Geophysics (Cambridge University Press, 1997)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Geological SciencesUniversity of Texas at El PasoEl PasoUSA
  2. 2.Geomedia Research and DevelopmentEl PasoUSA

Personalised recommendations