Pattern definition and pattern tracing in 4D GeoPET data sets from transport process studies
Risk assessment for deep geological repositories for radioactive and otherwise hazardous waste is a major task of public interest for decades (or centuries) to come. For fluid materials or particles in suspension, risk assessment hinges on knowing the details of their flow behavior, i.e. the flow velocity and the distribution of the liquid within a geosystem.
Conventional transport studies in geological media however, are mostly limited to analyzing breakthrough curves, but using PET (Positron Emission Tomography), we are able to measure fluid distribution within rock.
The aim of this thesis is to develop methods and code to quantitatively analyze fluid flow in geological media using PET time series, as well as parametrize the extracted flow phenomena to find characteristic and predictive parameters that are associated with different types of rock or soil.