Was the Deepwater Horizon Well Discharge Churn Flow? Implications on the Estimation of the Oil Discharge and Droplet Size Distribution

Boufadel, Michel C.; Gao, Feng; Zhao, Lin; Özgökmen, Tamay M.; Miller, Richard S.; King, Thomas; Robinson, Brian; Lee, Kenneth; Leifer, Ira

doi:10.1002/2017gl076606

Cited by 28 publications

(14 citation statements)

References 42 publications

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“…These observations allow researchers and response modelers to better calibrate their models for the conditions at hand. In situations where the volumetric flow rate of gas in the release is comparable to that of the liquid oil, churn flow is likely to occur, and it consists of the oil and gas tumbling within the pipe prior to release (Boufadel et al [133]). In this situation, models for predicting the oil DSD do not exist, but efforts for amending the VDROPJ model for this function are ongoing based on new experimental work.…”

Section: Droplet Sizementioning

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: Droplet Sizementioning

confidence: 99%

Progress in Operational Modeling in Support of Oil Spill Response

Barker

Kourafalou

Beegle-Krause

et al. 2020

JMSE

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“…This study therefore provides the first quantitative insight as to whether SSDI is an effective control method during the turbulent release of live oil in the deep-sea. Highly turbulent mixing at the wellhead may have generated natural dispersion (Aman et al, 2015;Boufadel et al, 2018). At the same time, the oil continued to surface near the DWH response site even under high SSDI volumes, presumably displacing the rising oil downstream (Socolofsky et al, 2015).…”

Section: Discussionmentioning

confidence: 99%

BP Gulf Science Data Reveals Ineffectual Subsea Dispersant Injection for the Macondo Blowout

et al. 2018

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After the Deepwater Horizon oil platform explosion, an estimated 172.2 million gallons of gas-saturated oil was discharged uncontrollably into the Gulf of Mexico, causing the largest deep-sea blowout in history. In an attempt to keep the oil submerged, massive quantities of the chemical dispersant Corexit R 9500 were deployed 1522 m deep at the gushing riser pipe of the Macondo prospect's wellhead. Understanding the effectiveness of this unprecedented subsea dispersant injection (SSDI) is critical because deepwater drilling is increasing worldwide. Here we use the comprehensive BP Gulf Science Data (GSD) to quantify petroleum dynamics throughout the 87-day long blowout. The spatio-temporal distribution of petroleum hydrocarbons revealed consistent higher concentrations at the sea surface and in a deep intrusion below 1000 m. The relative importance of these two layers depended on the hydrocarbon mass fractions as expected from their partitioning along temperature and pressure changes. Further, analyses of water column polycyclic aromatic hydrocarbons (PAH) of GSD extensively sampled within a 10-km radius of the blowout source demonstrated that substantial amounts of oil continued to surface near the response site, with no significant effect of SSDI volume on PAH vertical distribution and concentration. The turbulent energy associated with the spewing of gas-saturated oil at the deep-sea blowout may have minimized the effectiveness of the SSDI response approach. Given the potential for toxic chemical dispersants to cause environmental damage by increasing oil bioavailability and toxicity while suppressing its biodegradation, unrestricted SSDI application in response to deep-sea blowout is highly questionable. More efforts are required to inform response plans in future oil spills.

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“…Results of some droplet size experiments and models upon which the existing CRAs are based (e.g. results of V-DROP-J, ASA and SINTEF droplet size models; [1,9,10]) conflict with yet other experiments and models, especially those including 'live' (gas-saturated) oil at ambient deep sea pressures (∼15 MPa) that show a substantial fraction of small droplets [11,12] without the addition SSDI.…”

Section: Oil Droplet Physicsmentioning

confidence: 99%

“…A variety of models have been used to predict droplet diameter and fate with and without the use of dispersants (e.g. the VDROP-J, SINTEF, ASA and oil-CMS [1,9,10,12,14]). Contingent on the sub-set of experimental data chosen for incorporation in the models, the fraction of oil accumulating in deep plumes as a result of the application varies significantly.…”

Section: Research To Datementioning

confidence: 99%