Modeling Distribution, Fate, and Concentrations of Deepwater Horizon Oil in Subsurface Waters of the Gulf of Mexico

French-McCay, Deborah; Horn, Matthew; Li, Zhengkai; Jayko, K.; Spaulding, Malcolm L.; Crowley, Deborah; Mendelsohn, Daniel

doi:10.1016/b978-0-12-804434-6.00031-8

Cited by 24 publications

(18 citation statements)

References 58 publications

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“…Predictions of oil droplet size and the amount of hydrocarbons trapped and degraded in the subsea, floating on the ocean surface, and volatilized to the atmosphere are critical to discussions on environmental, health, and safety trade-offs related to the potential use of SSDI. Initial model predictions can be refined as monitoring data become available, but numerical simulations of a hypothetical deep-water blowout suggest the mitigative effects of SSDI are greatest when the strategy is implemented as soon as possible (French-McCay et al [95,96]). Response plans in the U.S. Gulf of Mexico envision that SSDI would become operational approximately six days into a loss of well control incident, barring complexities in clearing the working area of debris, so model output will be used to fill many information gaps in the short time when go/no-go decisions must be made.…”

Section: Operational Considerationsmentioning

confidence: 99%

Progress in Operational Modeling in Support of Oil Spill Response

Barker

Kourafalou

Beegle-Krause

et al. 2020

JMSE

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Following the 2010 Deepwater Horizon accident of a massive blow-out in the Gulf of Mexico, scientists from government, industry, and academia collaborated to advance oil spill modeling and share best practices in model algorithms, parameterizations, and application protocols. This synergy was greatly enhanced by research funded under the Gulf of Mexico Research Initiative (GoMRI), a 10-year enterprise that allowed unprecedented collection of observations and data products, novel experiments, and international collaborations that focused on the Gulf of Mexico, but resulted in the generation of scientific findings and tools of broader value. Operational oil spill modeling greatly benefited from research during the GoMRI decade. This paper provides a comprehensive synthesis of the related scientific advances, remaining challenges, and future outlook. Two main modeling components are discussed: Ocean circulation and oil spill models, to provide details on all attributes that contribute to the success and limitations of the integrated oil spill forecasts. These forecasts are discussed in tandem with uncertainty factors and methods to mitigate them. The paper focuses on operational aspects of oil spill modeling and forecasting, including examples of international operational center practices, observational needs, communication protocols, and promising new methodologies.

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Section: Operational Considerationsmentioning

confidence: 99%

Progress in Operational Modeling in Support of Oil Spill Response

Barker

Kourafalou

Beegle-Krause

et al. 2020

JMSE

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“…Sampling was constrained within 75 km from the wellhead and was extended beyond 75 km only after September, but the potential oil impacted region may have already moved beyond 75 km before September. According to [40], the average southwest current velocity at 900 m depth was approximately 0.067 ± 0.047 m/s. Based on this velocity, the oil released at the beginning of the spill may have traveled to~70-200 km away from the well head by 30 May.…”

Section: Discussionmentioning

confidence: 99%

“…On the contrary, the probabilistic model (e.g., SOSim [38,39]) uses probabilistic theory to make predictions based on the observations on submerged oil concentrations. All these models provide time updated predictions on submerged oil locations and concentrations [40]. However, the ocean current information needed by the deterministic model is usually provided by an external hydrodynamic model, thus the deterministic model's predictions are sensitive to the accuracy of hydrodynamic models [40].…”

Section: Modelingmentioning

confidence: 99%

“…All these models provide time updated predictions on submerged oil locations and concentrations [40]. However, the ocean current information needed by the deterministic model is usually provided by an external hydrodynamic model, thus the deterministic model's predictions are sensitive to the accuracy of hydrodynamic models [40]. Meanwhile, the probabilistic models only provide relative concentrations and the model accuracy relies on the quality and quantity of field observations.…”

Section: Modelingmentioning

confidence: 99%

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Formation, Detection, and Modeling of Submerged Oil: A Review

Beegle-Krause

Englehardt

2020

JMSE

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Submerged oil, oil in the water column (neither at the surface nor on the bottom), was found in the form of oil droplet layers in the mid depths between 900–1300 m in the Gulf of Mexico during and following the Deepwater Horizon oil spill. The subsurface peeling layers of submerged oil droplets were released from the well blowout plume and moved along constant density layers (also known as isopycnals) in the ocean. The submerged oil layers were a challenge to locate during the oil spill response. To better understand and find submerged oil layers, we review the mechanisms of submerged oil formation, along with detection methods and modeling techniques. The principle formation mechanisms under stratified and cross-current conditions and the concepts for determining the depths of the submerged oil layers are reviewed. Real-time in situ detection methods and various sensors were used to reveal submerged oil characteristics, e.g., colored dissolved organic matter and dissolved oxygen levels. Models are used to locate and to predict the trajectories and concentrations of submerged oil. These include deterministic models based on hydrodynamical theory, and probabilistic models exploiting statistical theory. The theoretical foundations, model inputs and the applicability of these models during the Deepwater Horizon oil spill are reviewed, including the pros and cons of these two types of models. Deterministic models provide a comprehensive prediction on the concentrations of the submerged oil and may be calibrated using the field data. Probabilistic models utilize the field observations but only provide the relative concentrations of the submerged oil and potential future locations. We find that the combination of a probabilistic integration of real-time detection with trajectory model output appears to be a promising approach to support emergency response efforts in locating and tracking submerged oil in the field.

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“…OpenOil is a fully fledged three-dimensional oil drift and fate model and has been evaluated against drifter and oil slick observations in the North Sea [43,44]. OpenOil is used as the operational model for oil spill response in Norway (as well as several international applications, e.g., EU Copernicus NOOS-Drift ensemble service, https://odnature.naturalsciences.be/noosdrift/) and has many of the characteristics of planning and preparedness models (such as the SIMAP model from RPS/ASA [45,46] and the TAP model from NOAA [47]). The OpenOil model has recently shown an excellent agreement with satellite observations of the DeepWater Horizon oil slick for two seven-day simulations forced by the oceanic and meteorological outputs (including waves) from the high resolution GoM-HYCOM 1/50 (in the GoM), FKEYS-HYCOM 1/100 (in the Straits), and ECMWF models [19].…”

Section: Oil Spill Simulationsmentioning

confidence: 99%

Pathways of Oil Spills from Potential Cuban Offshore Exploration: Influence of Ocean Circulation

Androulidakis

Kourafalou

Hole

et al. 2020

JMSE

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The DeepWater Horizon oil spill in the Gulf of Mexico (GoM) in 2010 raised the public awareness on potential spills from offshore exploration activities. It became apparent that knowledge of potential oil pathways in the case of a spill is important for preparedness and response. This study focuses on such scenarios from potential oil spills in the Cuban Exclusive Economic Zone (EEZ), a vast area in the GoM and the Straits of Florida that has not received much attention in oil spill studies, even though this region has been under evaluation for oil exploration. The Cuban EEZ is also in the crossroads of heavy tanker traffic, from the areas of intense oil exploration in the Northern GoM to the adjacent Caribbean Sea and Atlantic Ocean. The study also evaluates how the oil transport and fate are influenced by the main circulation patterns of the GoM, such as the Loop Current (LC) system and the mesoscale dynamics inside the Straits of Florida, such as the Florida Current (FC) and the accompanying cyclonic (along the northern Straits) and anticyclonic (along the Cuban coasts) eddies. We used oil spill numerical simulations, in tandem with high resolution data-assimilative ocean simulations, to test the fate of potential oil spills originating from different release sites within the Cuban EEZ during a six-year period (2011–2016) to exhibit certain aspects of interannual variability of ocean dynamics. The LC extended and retracted phases in the GoM interior revealed different impacts on the oil fate depending on the release site. The meandering of the FC, which is strongly related to the mesoscale eddies that evolve inside the Straits of Florida, controlled oil pathways either towards the northern Straits or along the Cuban coast. The most likely scenario for oil stranding at southern Florida is from oil released at the deep central Straits of Florida. Oil release near the Yucatan Strait and in the deep Gulf interior showed the highest risk of overall oil beaching at the Gulf beaches. The regional (e.g., LC) and local (e.g., eddies in the Straits) dynamics are proven to be significant indicators to predict the oil fate and stranding along the Gulf coasts, which should lead to improving planning and preparedness in the case of a spill in the Cuban EEZ.

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Modeling Distribution, Fate, and Concentrations of Deepwater Horizon Oil in Subsurface Waters of the Gulf of Mexico

Cited by 24 publications

References 58 publications

Progress in Operational Modeling in Support of Oil Spill Response

Progress in Operational Modeling in Support of Oil Spill Response

Formation, Detection, and Modeling of Submerged Oil: A Review

Pathways of Oil Spills from Potential Cuban Offshore Exploration: Influence of Ocean Circulation

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