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GEOSTATS: Combining different 3D-conditional simulations

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  • Coen van Tooren
    Hello to all, I have some problems in combining the results of conditional simulations of different variables. This is my problem: With the help of a model I m
    Message 1 of 1 , Sep 9, 1997
      Hello to all,

      I have some problems in combining the results of
      conditional simulations of different variables. This is
      my problem: With the help of a model I'm trying to
      estimate the variance of remediation costs of
      contaminated sites. The costs are calculated using an
      estimation of the 3-D spatial distribution of the
      contamination. The variance in the costs is due to the
      uncertainty of the estimations of the concentrations
      of the contaminants in unsampled points.
      To estimate the distribution of the pollutant the
      polluted area is devided in cubes of soil of a certain
      area and depth and then the concentration of the
      contaminant is estimated for each of these cubes.
      This is done for several different contaminants.
      For each cube the cost model determines the most
      polluting contaminant and this determines the
      contamination-class the cube is assigned to. This class
      determines the further use/processing of the soil in the
      cube, which is linked with certain known costs.
      Furthermore for each column of soil the depth till
      which the soil should be digged up is determined so all
      contamination till a certain level will be removed. This
      then determines the costs for digging; the deeper the
      higher the costs.

      To estimate the remediation costs and its variance I
      want to use 3D- conditional simulations of the
      distributions of the pollutants. For each pollutant
      separately concentrations are simulated for all
      cubes several times.
      Now one of the problems is how to combine the
      simulations of the different substances in the cost
      model. When combining the simulations of e.g. five
      pollutants, it's very likely that in every cube the
      concentration of (at least) one of the substances
      regarded will be estimated/simulated relatively high
      and as the most polluting substance determines the
      processing costs the estimated costs will be
      relatively high. The more pollutants are regarded the
      higher the estimated costs will be.
      The same applies for the number of layers
      distinguished. The more layers are distinguished in the
      simulation the higher the risk that at greater depth the
      simulated value will exceed a certain limit and the soil
      should be digged up which results in higher costs, i.e.
      the more layers the higher the estimated costs.

      Who has been dealing with these problems before and
      who has any suggestions on how to tackle
      these problems? We have been thinking about using
      Principal Component Analysis to reduce the
      multivariate problem into a univariate problem
      (simulating only the first Principal Component), but
      we're afraid of loosing a lot of information.

      Maaike Broos
      E-mail: imcoto@...

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