A data-driven traffic modeling for analyzing the impacts of a freight departure time shift policy

This paper proposes a data-driven transport modeling framework to assess the impact of freight departure time shift policies. We develop and apply the framework around the case of the port of Rotterdam. Container transport demand data and traffic data from the surrounding network are used as inputs. The model is based on a graph convolutional...

From time-lapse seismic inversion to history matching of water flooded oil reservoirs

The world energy demand still increases every year. As a consequence, the demand for fossil fuels, by far the first energy source, is increasing, while easily accessible fossil fuel resources are decreasing. This has stimulated research and development to the optimization of hydrocarbon recovery from existing reservoirs over the last decade....

Modeling and Inversion of Scattered Surface waves

In this thesis, we present a modeling method based on a domain-type integral representation for waves propagating along the surface of the Earth which have been scattered in the vicinity of the source or the receivers. Using this model as starting point, we formulate an inversion scheme to estimate properties of scattering objects close to the...