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Abstract

Summary

A multivariate statistical approach is presented to estimate water saturation in shallow heterogeneous formations. An improved factor analysis algorithm is developed to process engineering geophysical sounding data in a more reliable way. Resistivity and nuclear data acquired by cone penetration tools equipped with geophysical sensors are processed simultaneously to give an estimate to factor logs. The new factor analysis procedure is based on the iterative reweighting of data prediction errors using the highly robust most frequent value method, which improves the accuracy of factor scores in case of non-Gaussian data sets. A strong exponential relationship is detected between water saturation and the first factor log. Tests made on penetration logs measured from a Hungarian well demonstrate the feasibility of the most frequent value based factor analysis approach, which is verified by the results of local inverse modeling.

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/content/papers/10.3997/2214-4609.201600796
2016-05-30
2024-04-20

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References

  1. Drahos, D.
    [2005] Inversion of engineering geophysical penetration sounding logs measured along a profile. Acta Geodetica et Geophysica Hungarica, 40, 193–202.
     [Google Scholar]
  2. Fejes, I., Jósa, E.
    [1990] The engineering geophysical sounding method. Principles, instrumentation, and computerised interpretation. In: S.H.Ward (Ed.) Geotechnical and environmental geophysics, 2, Environmental and groundwater: SEG, 321–331.
     [Google Scholar]
  3. Jöreskog, K.G.
    [2007] Factor analysis and its extensions. In: R.Cudeck and R.C.MacCallum (Eds) Factor analysis at 100, historical developments and future directions. Lawrence Erlbaum Associates, Publishers, 47–77.
     [Google Scholar]
  4. Lawley, D.N., MaxwellA.E.
    [1962] Factor analysis as a statistical method. The Statistician, 12, 209–229.
     [Google Scholar]
  5. SteinerF.
    [1991] The most frequent value. Introduction to a modern conception of statistics. Academic Press, Budapest.
     [Google Scholar]
  6. SzabóN.P., DobrókaM., DrahosD.
    [2012] Factor analysis of engineering geophysical sounding data for water saturation estimation in shallow formations. Geophysics, 77, WA35–WA44.
     [Google Scholar]
  7. SzegediH. and DobrókaM.
    [2014] On the use of Steiner’s weights in inversion-based Fourier transformation: robustification of a previously published algorithm. Acta Geodaetica et Geophysica, 49, 95–104.
     [Google Scholar]
  8. Turai, E.
    [2011] Data processing method developments using tau-transformation of time domain IP data (II) - Interpretation results of field measured data. Acta Geodaetica et Geophysica, 46, 391–400.
     [Google Scholar]
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Most Frequent Value Based Factor Analysis of Engineering Geophysical Sounding Logs
Conference Proceedings 2016, 1 (2016); https://doi.org/10.3997/2214-4609.201600796
/content/papers/10.3997/2214-4609.201600796
/content/papers/10.3997/2214-4609.201600796
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