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[ai-geostats] sisim and SK vs. OK

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  • ewbhark@yahoo.com
    Hello all. I m performing unconditional sequential indicator simulation over a 3D domain. As the method requires, I have specified the data cdf at (10)
    Message 1 of 2 , Jan 3, 2005
      Hello all. I'm performing unconditional sequential indicator simulation over a 3D domain. As the method requires, I have specified the data cdf at (10) thresholds, and have also defined parameters for an (exponential) variogram at each threshold. When I run the simulation algorithm using simple kriging to estimate the cdf at each threshold for each node, the method works great, i.e., I am able to approximatley reproduce the domain cdf and variograms. However, when I use ordinary kriging, the method falls apart. It seems that reproduction of the domain cdf becomes 'blocky' and looses its smoothness. I have made the search ellipsoid very large and allowed the number of data points that can be used for the OK to be very large, but the results are always poor. Does anyone have any suggestions about what is happening with the OK? I am using GSLib software. Thanks to all!

      Eric Bhark
    • Pierre Goovaerts
      Hi Eric, I am guessing that the sampling density in 3D is small, hence at the beginning of the simulation procedure when the grid is essentially empty the
      Message 2 of 2 , Jan 3, 2005
        Hi Eric,

        I am guessing that the sampling density in 3D is small, hence
        at the beginning of the simulation procedure when the grid is
        essentially empty the estimate depends mainly on the type of trend
        model you adopt, i.e. a global mean for SK or a locally re-estimated
        local mean for OK. It looks like your estimate of the local mean
        is not very good and this might biase your simulation right from
        the beginning. Are you using a multiple grid strategy and did you
        notice a higher proportion of order relation deviations when using OK
        versus SK? Note that in the recent Stanford software GEMS, sequential
        indicator simulation is available only with the SK option, which
        might indicate some problems with the OK option...

        Hope it helps,

        Pierre
        <><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><>

        Dr. Pierre Goovaerts
        President of PGeostat, LLC
        Chief Scientist with Biomedware Inc.
        710 Ridgemont Lane
        Ann Arbor, Michigan, 48103-1535, U.S.A.

        E-mail: goovaerts@...
        Phone: (734) 668-9900
        Fax: (734) 668-7788
        http://home.comcast.net/~goovaerts/

        <><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><>

        On Mon, 3 Jan 2005 ewbhark@... wrote:

        > Hello all. I'm performing unconditional sequential indicator simulation over a 3D domain. As the method requires, I have specified the data cdf at (10) thresholds, and have also defined parameters for an (exponential) variogram at each threshold. When I run the simulation algorithm using simple kriging to estimate the cdf at each threshold for each node, the method works great, i.e., I am able to approximatley reproduce the domain cdf and variograms. However, when I use ordinary kriging, the method falls apart. It seems that reproduction of the domain cdf becomes 'blocky' and looses its smoothness. I have made the search ellipsoid very large and allowed the number of data points that can be used for the OK to be very large, but the results are always poor. Does anyone have any suggestions about what is happening with the OK? I am using GSLib software. Thanks to all!
        >
        > Eric Bhark
        >
        >
        >
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