2D mapping of radiological contaminations using geostatistics

• Understand and master the use of geostatistics solutions to characterize and map in 2D radiological contaminations (soils and building structures).
• Design and optimize the sampling strategy to reduce estimation uncertainties.
• Classify contaminated areas according to radiological thresholds.

• Half of the course is devoted to methodological presentations, the second half to practical exercises on real-life cases to deepen the understanding of concepts. The focus is on illustrations and practical contributions of the covered concepts.
• Computer exercises with Kartotrak.
• Course material provided.

Engineers, technicians, consultancies, project owners, public bodies, industrial operators who wish a practical introduction to the geostatistical methods for radiological contamination characterization.

DAY 1: ANALYSE DATA AND THEIR VARIABILITY IN SPACE

• Better understand radiological data and put them back in their environmental context: taking into account historical and contextual data (zone of interest, aerial views, Digital Elevation model, etc.) and 2D visualization.
• Validate data: use of statistical methods for data analysis and quality control.
• Understand the concept of spatial variability and the operational implications for the sampling stage on the one hand and remediation options on the other side.
• Quantify the spatial continuity of the contamination: calculation, interpretation, and modeling of the variogram.

DAY 2: CONTAMINATION MAPPING AND SURFACE CLASSIFICATION.

• Understand the principles and properties of 2D kriging and implement this sound interpolation technique for an appropriate mapping of the surface contamination.
• Use estimation uncertainty results to identify the areas which require further characterization.
• Classify contaminated areas according to radiological thresholds.
• Be introduced to depth profiles (soils and concrete) and consequences on 3D geostatistical modeling.

This course does not require prior knowledge in geostatistics.

This course can also be followed by an “à la carte” workshop based on your own data.