• To investigate the selection of met-ocean oil spill scenarios by means of data mining techniques, taking into account deep (near-field) and water column and surface process (far-field).
• To further advance in the probabilistic application of 3D oil spill numerical models by means of coupling near and fard-field models, implementation of cross-scale process and simulation by ensembles.
• Application of Markov chains and autoregressive logistic models for hazard assessment of the aforementioned oil spills.
• Development of methodologies based on: met-ocean hindcast databases; data mining techniques and Weather Typing Schemes; Markov chains and autoregressive logistic models; near-field and far-field oil spill numerical modelling (3D).
• Statistical analysis based on the guideline of oil spill risk assement and response planning of offshore instalations, with the aim of providing the probability of contamination in the sea bottom, water column, sea surface and shoreline.
• Application of the methodology to the Deepwater Horizon and comparison of the results with existing data from the bibliography about the Deepwater Horizon well blowout (Mexican Gufl, 2010).