Training
An overview of geostatistics for radiological characterization
Objectives
Understand why geostatistics is relevant to radiological characterization and how it can support decommissioning decisions. You will see how spatial variability affects sampling and remediation feasibility, how kriging supports contamination mapping and uncertainty assessment, and how stochastic simulations help estimate contaminated volumes and evaluate the local risk of exceeding cleanup levels.
Target audience
Stakeholders who plan, manage, or assess nuclear decommissioning projects and need to understand how geostatistics can support radiological characterization and remediation decisions
Content
Understand why spatial heterogeneity matters
– Compare the advantages, limitations, and underlying assumptions of the usual approaches to radiological characterization.
– Discover how a variogram describes the heterogeneity and spatial variability of pollutants.
– Understand how spatial variability can affect the feasibility of remediation techniques.
Improve the prediction and mapping of radiological contamination
– See how kriging accounts for spatial variability to provide the best estimate and quantify its associated uncertainty.
– Understand how site history, qualitative observations, and on-site measurements can be incorporated as ancillary information.
Quantify and locate contaminated volumes
– Discover how stochastic simulations represent the spatial variability of contamination.
– See how the results provide a global estimate of contaminated volumes and the associated uncertainty.
– Assess the local risk of exceeding cleanup levels.
Use geostatistics to optimize site investigation plans
– Understand the relationship between the evaluation objective, sampling strategy, and data-processing approach.
– Review the spatial structures observed in radiological contamination.
– Examine how degraded sampling or multivariate treatment affects uncertainty.
Key points
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 use. Feedback and discussions.
Prerequisites
None.
The trainer
Meryem Meziane, PhD
Consultant, Geostatistics & Environment
Drawing on doctoral research in geostatistics applied to nuclear safety at ASNR and teaching experience at Mines Paris–PSL and Université Paris Cité, Meryem supports clients in implementing Kartotrak. She turns sampling data into reliable 3D contamination models, defensible volume estimates, and robust remediation decisions, tailored to the challenges of contaminated sites and nuclear decommissioning.
Register, or ask us first
This form handles all three: registration, a quote for yourself or your team, and questions about the content or the prerequisites.
Address
44 Avenue de Valvins, 77210 Avon, France