The main objective of this study is to highlight the utility of geostatistics for polluted soil remediation purposes. The second objective of this project was more practical one. It consists on the identification of areas that should be subjected to remedial actions and also on deciding which contaminant needs to be considered when remediation processes are taken. To achieve the described objectives, a contaminated site has been studied and the following steps have been followed: The contamination concentration limits beyond which action needs to be taken to remediate the ground contamination, in which case it is important to determine the areas that should be subjected to the appropriate remediation measures. A presentation of a case study will follow. A brief site description is given. Next, a spatial analysis of the site has been carried out. It consists essentially of: Firstly a primary process of the data which means that histograms and an unprocessed representation of the pollutant’s distribution has been plotted for each contaminant. Secondly a graphic presentation of the pollution using inverse distance weight (IDW) and Kriging interpolation technique is shown. This research is exploring the possibility of stochastic simulation to produce more realistic image of the data distribution, compared with kriging errors .Finally an assessment concerning Kriging is presented and a balance between the advantages and disadvantages of its uses is discussed.
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