An overview of geostatistics for radiological characterization
Find out why the geostatistical approach is relevant for radiological characterization, what its added value and application conditions are.
DURATION: 1 DAY | LEVEL: AWARENESS
This one-day seminar presents the added value of geostatistics for radiological characterization of nuclear facilities under decommissioning and contaminated sites, taking into account site history, sampling optimization, in-situ radiation mapping and contaminated volume classification.
Methodological exposition illustrated in the field of site clean-up / dismantling on numerous cases of application. Added value of the geostatistical methodology as well as its limits of application. Feedback and discussions.
Who should attend?
This course is aimed at project managers and decision-makers involved in decommissioning and dismantling projects who want a practical, synthetic and pragmatic introduction to geostatistical methods for radiological characterization.
Understanding and estimating the spatial heterogeneity of contamination
- Pros/Cons and underlying assumptions of the usual approaches for radiological characterization
- Practical introduction to the concepts of heterogeneity and spatial variability of pollutants (variogram)
- Operational consequences on the feasibility of given remediation techniques.
Predicting and mapping radiological contamination
- Introduction to kriging and its advantages taking into account spatial variability, best estimation, quantification of associated uncertainty
- Consideration of ancillary information: site history, qualitative observations and on-site measurements.
Quantify and locate contaminated volumes
- Practical introduction to stochastic simulations
- Presentation of results: global estimation of contaminated volumes and attached uncertainty, local risk of exceeding cleanup levels.
Recommendations for the optimization of site investigation plans
- Implementation of the triptych: Evaluation objective – Sampling strategy – Data processing
- Feedback on the spatial structures of radiological contamination
- Impact on uncertainties with degradation of sampling or multivariate treatment