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Re: GEOSTATS: Geostat: Program for Bimodal distribution.

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  • Romijn, R.
    Message 1 of 3 , Mar 23, 2000
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      Re: GEOSTATS: Geostat: Program for Bimodal distribution.

      Dear Eunjeong Seok,

      A semivariogram of a bimodal distribution reflects two kinds of variances: 1) the spatial variance between the sample points and 2) the variance between the two populations which form the bimodel distribution. The spatial variance is therefore contaminated with the variance between the two populations.

      One thing you can do is try to identify the factors related to these two populations. When these factors are determined (e.g. mineral composition, direction etc. ) you can correct your data points in such a way the distribution becomes unimodal. A semivariogram of this unimodal distribution wil reflect the spatial variance with less contamination. For the new variogrammodel GSlib is appropriate.

      A second way to handle the problem is simply to do two interpolations of the datapoints of the two populations separately and then subsequently combine these two interpolation results. The drawback of this method is that the number of datapoints per interpolation will be reduced.

      Good luck,

      Guido Ypenburg


      G.C. Ypenburg
      Engenering department
      Public Works Rotterdam
      Hydrogeology and geostatistics
      Galvanistraat 15
      PO box 6633
      3002 AP Rotterdam
      tel:    +31 10-489 54 97
      fax:    +31 10-489 45 00

        Van:    Pieters, G.
        Verzonden:      woensdag 22 maart 2000 8:35
        Aan:    Ypenburg, G.
        Onderwerp:      FW: GEOSTATS: Geostat: Program for Bimodal distribution.

        Van:    Eunjeong Seok[SMTP:ESEOK@...]
        Verzonden:      woensdag 22 maart 2000 4:49:34
        Aan:    ai-geostats@...
        Onderwerp:      GEOSTATS: Geostat: Program for Bimodal distribution.
        Automatisch doorgezonden door een regel

        Could you post this, please. Thanks.


        I am struggling with an aperture data set of a fracture plane, which shows a
        bimodal distribution.

        I have tried Kriging and Gaussian simulation (GSLIB) to recover the aperture
        structure, but it seems not to maintain both variogram and mean and variance
        of the samples at the same time .

        Therefore, I wonder if there is any software which is able to deal with
        bimodal distribution, and
        If GSLIB is a right way to go, what kind of consideration do I need and
        which program is the most appropriate?

        Thank you in advance..

        Eunjeng Seok
        Dept. of Earth Sciences
        Memorial Univ. of NFLD
        St. John's, Canada
        Tel: 1-709-739-7270

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