Methods based on two-point geostatistics have been routinely used to interpolate random variables such as groundwater level and concentration and to estimate their values at un-sampled locations. These methods use the observed data to analyze spatial two-point correlations and ignore the higher order moments that may play a key role in the characterization of complex patterns. In this work, a multiple-point geostatistics method is applied to interpolate groundwater level data. To do this, the ensemble simulated groundwater level maps after modeling full physics are used as training images to derive the multiple correlations. An example shows the advantages of using multiple-point geostatistics compared with the traditional two-point geostatistics methods (such as Kriging) for the interpolation of groundwater level data in a complex geological formation.

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characterization of complex patterns unsampled full physics geological formation ensemble simulated groundwater level maps spatial twopoint correlations interpolation of groundwater level data in twopoint geostatistics methods higher order moments observed data interpolate random variables multiplepoint geostatistics method kriging

Liangping Li,Guanxing Huang,.Groundwater Level Mapping Using Multiple-Point Geostatistics. 8 (9),.

Liangping Li,Guanxing Huang,"Groundwater Level Mapping Using Multiple-Point Geostatistics" 8

Liangping Li,Guanxing Huang,"Groundwater Level Mapping Using Multiple-Point Geostatistics"