Oilmap: An Interactive Oil Spill Model

Jayko, K.; Howlett, Eoin

doi:10.1109/oceans.1992.612687

Cited by 3 publications

(2 citation statements)

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“…Among the activities conducted in a risk analysis, the study of the consequences of an oil spill, with the track of its trajectory and estimation of the final oil fate, is a complex task. It involves simulations using state of the art models like GNOME model (Beegle-Krause, 2005;Zelenke et al, 2012), BLOSOM (Sim et al, 2015;Duran, 2016), OSCAR (Reed et al, 1995), OILMAP (Jayko and Howlett, 1992;Spaulding et al, 1994), SIMAP (French, 1998;French-McCay, 2004) and other models (see reviews from Spaulding, 2017 andKeramea et al, 2021). The trajectory models usually simulate the oil as Lagrangian particles that drift according to the effects of seawater currents, wind and diffusion.…”

Section: Wind Drift Factor and Uncertainty Analysismentioning

confidence: 99%

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Estimation of the wind drift factor and uncertainty analysis based on CFD computer simulations

Sbragio

Martins

2023

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PurposeThe purpose of this work is to present a procedure for determining the wind drift factor through two-dimensional computational fluid dynamics (CFD) simulations of the wind acting on a wavy sea surface, such that the subjectivity of its estimation is reduced.Design/methodology/approachThe wind drift factor was determined by two-dimensional CFD analyses with open-channel condition. The characteristic wave was determined by the Sverdrup–Munk–Bretschneider (SMB) method. The uncertainty analysis is based on convergence studies using a single parameter refinement (grid and time step).FindingsThis procedure allows the estimation of the wind drift factor in a fetch-limited domain. The domain's value in the analyzed region is 0.0519 ± 4.92% which is consistent with the upper values of the wind drift factors reported in the literature.Research limitations/implicationsThe use of a three-dimensional domain was impractical with the available computational resources because of the fine mesh required for wave modeling. The uncertainty analysis consisted only of a verification procedure. Validation against real data was not possible because of the lack of measured data in the analyzed region.Originality/valueThe wind drift factor is usually estimated based on either experience or random sampling. The original contribution of this work is the presentation of a CFD procedure for estimating the wind drift factor, in which the domain inlet is subjected to a wave boundary condition and to a wind velocity.

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Section: Wind Drift Factor and Uncertainty Analysismentioning

confidence: 99%

“…, 2015; Duran, 2016), OSCAR (Reed et al. , 1995), OILMAP (Jayko and Howlett, 1992; Spaulding et al. , 1994), SIMAP (French, 1998; French-McCay, 2004) and other models (see reviews from Spaulding, 2017 and Keramea et al.…”

Section: Introductionmentioning

confidence: 99%

Estimation of the wind drift factor and uncertainty analysis based on CFD computer simulations

Sbragio

Martins

2023

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Bioremediation of Petroleum Hydrocarbons in Seawater: Oil Spill Plume Modelling Approaches

Benard

Tuah

2018

Microbial Action on Hydrocarbons

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Development of Oil Spill Scenarios for Contingency Planning Along the Brazilian Coast

Lima

Sartori

Yassuda

et al. 2003

International Oil Spill Conference Proceedings

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After an oil spill in Guanabara Bay due to the collapse of a marine fuel pipeline in January 2000, PETROBRAS (a Brazilian company among the 15 largest oil companies in the world) is facing important challenges regarding its environmental commitment to Brazilian society. To face these new challenges, PETROBRAS launched a program for excellence in environmental, health and safety management that includes the development of oil spill contingency plans for its facilities. The present paper describes an oil spill modeling project for 25 facilities along the Brazilian coast. The implementation of the project involved a detailed meteorological and oceanographic characterization of each study area with a review of existing data, data collection, and hydrodynamic modeling covering more than 9,000 km of coastline. Based on the requirement of scenarios for both typical and critical conditions, the oil fates and trajectory modeling system OILMAP was applied to simulate oil spill incidents in all 25 sites, most of them oil terminals from TRANSPETRO, a PETROBRAS subsidiary. Due to Brazil's continental dimensions, the environmental conditions simulated ranged from the subtropical Patos Lagoon in the southernmost part of the country to the equatorial Solimoes River, including estuaries, coastal zones, and offshore sites. The developed modeling system allows oil spill contingency specialists to develop response plans for typical spills in the selected locations. By performing reverse trajectory calculations from sensitive sites such as water intakes or fragile wetlands, it is also be possible to identify probable release locations of spills and principal avenues of vulnerability for these important resources. This paper presents a description of the implementation of the system and the results of this modeling approach for a typical oil terminal located in the city of Vitoria, eastern Brazilian coast.

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Oilmap: An Interactive Oil Spill Model

Cited by 3 publications

References 0 publications

Estimation of the wind drift factor and uncertainty analysis based on CFD computer simulations

Estimation of the wind drift factor and uncertainty analysis based on CFD computer simulations

Bioremediation of Petroleum Hydrocarbons in Seawater: Oil Spill Plume Modelling Approaches

Development of Oil Spill Scenarios for Contingency Planning Along the Brazilian Coast

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