Avances en metodologías estadísticas para la simulación en el medio-largo plazo de derrames de hidrocarburos en el mar

Resumo

The aim of this thesis is the improvement of existing tools for the fight against oil spill marine pollution. On the one side, we developed a methodology for the probabilistic forecast of oil spills at the mid-long term. The core of the methodology is the statistical simulation of oil spill met-ocean forcings, using a logistic regression model. Logistic regression modeling of met-ocean patterns is applied in the Gulf of Mexico and in the Bay of Biscay. In the second case, mid-long term prediction of oil spill is achieved considering the statistically simulated met-ocean conditions. On the other hand, we proposed a methodology for deep oil spill hazard assessment, based on the selection of spatio-temporal met-ocean patterns. This methodology was applied in the North Sea, and the obtained results were compared with the ones achieved with a traditional hazard estimation technique, highlighting the benefit of the proposed method. The methodologies presented in this thesis have shown their ability and the benefits they could bring to the tools for the fight against marine pollution.