Small-scale experiments performed at SINTEF, Norway in 2011–12 led to the development of a modified Weber scaling algorithm. The algorithm predicts initial oil droplet sizes (d50) from a subsea oil and gas blowout. It was quickly implemented in a high number of operational oil spill models used to predict fate and effect of subsea oil releases both in academia and in the oil industry. This paper presents experimental data from large-scale experiments generating oil droplet data in a more realistic multi-millimeter size range for a subsea blow-out. This new data shows a very high correlation with predictions from the modified Weber scaling algorithm both for untreated oil and oil treated by dispersant injection. This finding is opposed to earlier studies predicting significantly smaller droplets, using a similar approach for estimating droplet sizes, but with calibration coefficients that we mean are not representative of the turbulence present in such releases. | publishedVersion

The explosion of the Deepwater Horizon oil platform on April 20th, 2010 resulted in the second largest oil spill in history. The distribution and chemical composition of hydrocarbons within a 45 km radius of the blowout was investigated. All available certified hydrocarbon data were acquired from NOAA and BP. The distribution of hydrocarbons was found to be dispersed over a wider area in subsurface waters than previously predicted or reported. A deepwater hydrocarbon plume predicted by models was verified and additional plumes were identified. Because the samples were not collected systematically, there is still some question about the presence and persistence of an 865 m depth plume predicted by models. Water soluble compounds were extracted from the rising oil in deepwater, and were found at potentially toxic levels outside of areas previously reported to contain hydrocarbons. Application of subsurface dispersants was found to increase hydrocarbon concentration in subsurface waters.

This study investigated the sensitivity of two deepsea species using mortality of northern shrimp (Pandalus borealis) and polyp activity of stony coral (Lophelia pertusa) to dispersant, Corexit 9500 and aromatic hydrocarbons (toluene, 2-methylnaphthalene, phenanthrene) in 96-h tests. Resulting hydrocarbon toxicity data were fit to the Target Lipid Model to generate predictive models and determine species sensitivity. Toxicity of chemically enhanced water accommodated fractions of Alaskan North Slope crude oil (ANS-oil) was also investigated with shrimp using nominal loading, total petroleum hydrocarbons and biomimetic extraction (BE) as oil exposure metrics. Coral were more sensitive to dispersant than shrimp while similar sensitivity was observed for hydrocarbons. Study and literature findings indicate deepsea species exhibit acute sensitivities to dispersant, hydrocarbons and oil that are comparable to pelagic species. Results support use of passive sampling methods to quantify dissolved oil for interpreting oil toxicity tests and suggest models for predicting time-dependence of toxicity warrant re-evaluation.

Species-level variability has made it difficult to determine the relative sensitivity of phytoplankton to oil and mixtures of oil and dispersant. Here we develop a phytoplankton group sensitivity index using ribosome sequence data that we apply to a mesocosm experiment in which a natural microbial community was exposed to oil and two oil-dispersant mixtures. The relative sensitivity of four phytoplankton taxonomic groups, diatoms, dinoflagellates, green algae, and Chrysophytes, was computed using the log of the ratio of the number of species that increase to the number that decrease in relative abundance in the treatment relative to the control. The index indicates that dinoflagellates are the most sensitive group to oil and oil-dispersant treatments while the Chrysophytes benefit under oil exposure compared to the other groups examined. The phytoplankton group sensitivity index can be generally applied to quantify and rank the relative sensitivity of diverse microbial groups to environmental conditions and pollutants.

Limited experimental and field data are available describing oil droplet formation from subsea releases at high pressure. There are also analytical challenges quantifying oil droplets over a wide size and concentrations range at high pressure. This study quantified oil droplets released from an orifice in seawater at low and high pressure (5 m and 1750 m depth). Oil droplet sizes were quantified using a newly developed sensor (Silhouette camera or SilCam).The droplet sizes measured during experiments at low and high pressure, using the same release conditions, showed no significant difference as a function of pressure. This lack of a pressure effect on oil droplet sizes was observed for both untreated oil and for droplet formation during subsea dispersant injection or SSDI. This strongly indicates that the effectiveness of SSDI is not influenced by water depth or pressure, at least for simulated subsea releases of oil alone (no gas).

The degree to which droplet shedding (tip-streaming) can modify the size of rising oil droplets has been a topic of growing interest in relation to subsea dispersant injection. We present an experimental and numerical approach predicting oil droplet shedding, covering a wide range of viscosities and interfacial tensions.Shedding was observed within a specific range of droplet sizes when the oil viscosity is sufficiently high and the IFT is sufficiently low. The affected droplets are observed to reduce in size, as smaller satellite droplets are shed, until the parent droplet reaches a stable size.Shedding of smaller droplets is related to the viscosity-dominated modified capillary number (Ca′), especially for low dispersant dosages recommended for subsea dispersant injection. This, in combination with the IFT-dominated Weber number (We), characterise droplets into three possible states: 1) stable (Ca′ < 0.21 &We<12); 2) tip-streaming (Ca′ > 0.21 &We<12); 3) unstable and subject to total breakup (We>12).

Underwater blowouts from gas and oil operations often involve the simultaneous release of oil and gas. Presence of gas bubbles in jets/plumes could greatly influence oil droplet formation. With the aim of understanding and quantifying the droplet formation from Deepwater Horizon blowout (DWH) we developed a new formulation for gas-oil interaction with jets/plumes. We used the jet-droplet formation model VDROP-J with the new module and the updated model was validated against laboratory and field experimental data. Application to DWH revealed that, in the absence of dispersant, gas input resulted in a reduction of d50 by up to 1.5mm, and maximum impact occurred at intermediate gas fractions (30–50%). In the presence of dispersant, reduction in d50 due to bubbles was small because of the promoted small sizes of both bubbles and droplets by surfactants. The new development could largely enhance the prediction and response to oil and gas blowouts.

Simulated column was applied to research forming progress of single oil droplet in submerged process, floating progress, and study effects of environment factors and dispersants on the concentration of oil hydrocarbon in water as well as changing rules of oil droplet sizes. As expected, particular formation mechanism of single oil droplet was presented. When necking down length L is 0.5 time of oil droplet diameter (d) after expansion phase, necking down becomes long and thin; when L=2d, necking down begins to break. In floating progress, the shape changes oval and its motion trail becomes an auger-type. Fluctuation occurs at horizontal direction. Dispersants decrease oil droplet size by its dispersion effect, and cut down effect of Van Der Waals force among oil droplets. More broadly, these findings provide rare empirical evidence expounding formation mechanism of single oil droplet to increasing ability of oil spill response.

Effectiveness of oil spill dispersants containing lecithin/Tween 80 (L/T) blends in ethanol was measured as a function of L:T ratio, surfactant:solvent ratio, solvent composition, and dispersant:oil ratio (DOR) using baffled flask dispersion effectiveness tests. Optimal L:T ratios are between 60:40 and 80:20 (w/w); at higher L:T ratios, effectiveness is limited by high interfacial tension, while at lower L:T ratios, insufficient lecithin is present to form a well-packed monolayer at an oil–water interface. These optimal L:T ratios retain high effectiveness at low DOR: 80:20 (w/w) L:T dispersant is 89% effective at 1:25 DOR (v/v) and 77% effective at 1:100 DOR (v/v). Increasing surfactant:solvent ratio increases dispersant effectiveness even when DOR is proportionally reduced to keep total surfactant concentration dosed into the oil constant. Replacing some of the ethanol with octane or octanol also increases dispersant effectiveness, suggesting that ethanol's hydrophilicity lowers dispersant–oil miscibility, and that more hydrophobic solvents would increase effectiveness.