Simulating and Predicting Offshore Oil Spills by Using Cellular Automata

Abstract

In recent years, offshore oil spill accidents have caused substantial damage to both marine organisms and marine ecology. Accurate simulation and prediction of oil spills could provide a scientific basis for assessing losses due to oil spills and provide support for emergency decisions regarding oil spills. We analyzed the advantages and disadvantages of existing oil spill models and constructed an offshore oil spill model based on cellular automata (CA). By considering both the flow field and wind field, we formulated new CA rules for the diffusion and drift of a pollution zone, and in our model, the cellular state in eight-neighborhood mode is updated in accordance with these rules, which makes the model suitable for dynamic simulation of offshore oil spills. We also constructed a model on the basis of fuzzy comprehensive evaluation for evaluating the oil spill grade. Finally, we developed a software system, the Ocean Oil Spill Information System (OOSIS), which includes all necessary functions such as basic operations, data management, information query, oil spill analysis, and oil spill assessment. OOSIS is used to verify the constructed oil spill model, and the sea breeze and current data from the National Oceanic and Atmospheric Administration were used to realize the dynamic simulation and prediction, grade evaluation, and cleanup plan generation for offshore oil spill.