3D visualization of geophysical resistivity data to delineate contamination anomalies in a landfill

Abstract

Geophysical data represent subsoil structure in a specific area and can be used to extract subsoil information for various purposes. In this work we used this data type to detect anomalies/contamination in the subsoil. Our case study was based on data acquired around a landfill and the main objective is identifying contaminated areas as a result of leakage in landfill. This involves the application of statistical methods to detect anomalous values taking into account the whole data set, subdividing it in sublevels in relation to the surface, instead of using a single threshold (as usual). This work combines in the same software package the anomaly statistical analysis and several 3D representations of the results to validate and also helps understanding the final results of the analysis. Given that the original data used in the analysis, resistivity sections, is normally very sparse, a kriging geostatistical process was used to interpolate data in order to provide a volumetric representation of the subsoil in the area, providing a continuous spatial visualization.