Mapping and estimation of contaminated volumes using geostatistics
Understand and master the use of geostatistical solutions for contamination mapping and the rigorous calculation of the volumes to be remediated.
DURATION: 3 DAYS | LEVEL: FUNDAMENTALS
- Understand and master the use of geostatistics solutions to characterize chemical pollution or radiological contamination.
- Generate robust contamination maps, with a quantified level of accuracy.
- Objectively delineate the impacted areas and quantify the uncertainty level associated with estimated volumes.
- 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. Focus is on illustrations and practical contribution of the covered concepts.
- Computer exercises with Kartotrak.
- Course material provided.
Who should attend
Engineers, technicians, consultancies, project owners, prime contractors, public bodies, industrial operators who wish a practical introduction to the geostatistical methods for pollution/contamination characterization.
Day 1: Analyse data and their variability in space
- Better understand pollution data and put them back in their environmental context: taking into account historical and contextual data (lithology, aerial views, Digital Elevation Model, etc.) and 2D/3D visualization.
- Validate data: use of statistical methods for data analysis and quality control (correlations, histograms, etc.).
- Understand the concept of spatial variability and the operational implications for the feasibility of some cleanup methods.
- Quantify the spatial variability of a pollutant: calculation, interpretation, and modeling of the variogram.
Day 2: Pollution/contamination mapping
- Discover usual interpolation methods and their limits of application.
- Understand the principles and properties of 2D and 3D kriging and implement the technique for a rigorous mapping of the pollution/contamination.
- Use kriging results to identify the areas which require further characterization.
- Take up multivariate geostatistics
Day 2: Quantify contaminated soil volumes
- Understand the difference between kriging and conditional simulations: why simulations are essential to a rigorous analysis of the uncertainties.
- Learn how to implement conditional simulations to:
– Generate probability maps of exceeding a regulatory threshold (2D/3D).
– Generate distribution curves of the surface/volume of soil requiring remediation according to the risk of exceeding a given threshold.
– Calculate the pollutant mass from soil density and pollutant concentration.
- Derive the surface, volume, and mass of soil requiring remediation according to the ‘’Pareto-Sol’’ principle.
- Generate the excavation maps from 3D interpolated contamination maps.
- Compare the efficiency of the different cleanup scenarii.