Probabilistic Modeling of Oil Spills at the Exclusive Economic Zone of Cuba Using Petromar-3D Model

This article shows the probabilistic modeling of hydrocarbon spills on the surface of the sea, using climatology data of oil spill trajectories yielded by applying the lagrangian model PETROMAR-3D. To achieve this goal, several computing and statistical tools were used to develop the probabilistic modeling solution based in the methodology of Guo. Solution was implemented using a databases approach and SQL language. A case study is presented which is based on a hypothetical spill in a location inside the Exclusive Economic Zone of Cuba. Important outputs and products of probabilistic modeling were obtained, which are very useful for decision-makers and operators in charge to face oil spill accidents and prepare contingency plans to minimize its effects. In order to study the relationship between the initial trajectory and the arrival of hydrocarbons spills to the coast, a new approach is introduced as an incoming perspective for modeling. It consists in storage in databases the direction of movement of the oil slick at the first 24 hours. The probabilistic modeling solution presented is of great importance for hazard studies of oil spills in Cuban coastal areas.

Lagrangian Model PETROMAR-3D to Describe Complex Processes in Marine Oil Spills

The version 2.1 of PETROMAR-3D model, created in the Center for Marine Meteorology of the Meteorology Institute of Cuba, is presented. This Lagrangian model has been designed to describe the physical processes of marine oil spills in the face of multiple scenarios of the marine environment. Although it is applicable to any part of the world, it is mainly designed for inter-American seas. The novelty has been to integrate the processes of drift and weathering into a model, with updated methods that incorporate 3D phenomena, a very favorable situation to achieve an operating system in Cuba and the region for the immediate and medium term. Python was chosen as the programming language because it has advanced libraries for numerical modeling, automation work and other useful tools for pre-and post-processing. By means of adapters, an important number of atmospheric, hydrodynamic and wave models have been considered to create the scenarios efficiently. The modular distribution in which the code has been created facilitates its use for other dispersion analysis and biophysical applications. Finally, a set of simple images are presented, aimed at informing decision-makers in order to mitigate the effects of the spill on the environment.

The influence of Stokes drift on oil spills:Sanchi oil spill case

Spilled oil floats and travels across the water’s surface under the influence of wind,currents,and wave action.Wave-induced Stokes drift is an important physical process that can affect surface water particles but that is currently absent from oil spill analyses.In this study,two methods are applied to determine the velocity of Stokes drift,the first calculates velocity from the wind-related formula based upon a one-dimensional frequency spectrum,while the second determines velocity directly from the wave model that was based on a twodimensional spectrum.The experimental results of numerous models indicated that:(1)oil simulations that include the influence of Stokes drift are more accurate than that those do not;(2)for medium and long-term simulations longer than two days or more,Stokes drift is a significant factor that should not be ignored,and its magnitude can reach about 2%of the wind speed;(3)the velocity of Stokes drift is related to the wind but is not linear.Therefore,Stokes drift cannot simply be replaced or substituted by simply increasing the wind drift factor,which can cause errors in oil spill projections;(4)the Stokes drift velocity obtained from the two-dimensional wave spectrum makes the oil spill simulation more accurate.

Oil Spill Dispersion Forecasting with the Aid of a 3D Simulation Model

The simulation of the transport and fate of an oil slick, accidentally introduced in the marine environment, is the focus of this research. An oil spill dispersion forecasting system （DIAVLOS forecasting system）, based on wind, wave and ocean circulation forecasting models is developed. The 3-D oil spill model, by the University of Thessaloniki, is based on a Lagrangian （tracer） model that accounts for the transport-diffusion-dispersion and physicochemical evolution of an oil slick. The high resolution meteorological, hydrodynamic and wave models are coupled with the operational systems ALERMO and SKIRON of the University of Athens. The modelling system was successfully assembled and tested under theoretical and realistic scenarios, in order to be applied in forecasting mode and be used by local authorities when an accident occurs. As a result, a 48-hours oil spill dispersion forecasting system was synthesized aiming primarily at the oil spill management at the Burgas-Alexandroupolis oil-pipe terminal, part of a greater busy coastal basin in North Aegean.

Modeling the Flow Regime Near the Source in Underwater Gas Releases

Recent progress in calculating gas bubble sizes in a plume, based on phenomenological approaches using the release conditions is a significant improvement to make the gas plume models self-reliant. Such calculations require details of conditions Near the Source of Plume （NSP）; （i.e. the plume/jet velocity and radius near the source）, which inspired the present work. Determining NSP conditions for gas plumes are far more complex than that for oil plumes due to the substantial density difference between gas and water. To calculate NSP conditions, modeling the early stage of the plume is important. A novel method of modeling the early stage of an underwater gas release is presented here. Major impact of the present work is to define the correct NSP conditions for underwater gas releases, which is not possible with available methods as those techniques are not based on the physics of flow region near the source of the plume/jet. We introduce super Gaussian profiles to model the density and velocity variations of the early stages of plume, coupled with the laws of fluid mechanics to define profile parameters. This new approach, models the velocity profile variation from near uniform, across the section at the release point to Gaussian some distance away. The comparisons show that experimental data agrees well with the computations.