Search

The Deepwater Horizon oil spill in the Gulf of Mexico in 2010 was the largest in US history, covering more than 1,000 km of shorelines and causing losses that exceeded $50 billion. While oil transformation processes are understood at the laboratory scale, the extent of the Deepwater Horizon spill made it challenging to integrate these processes in the field. This review tracks the Deepwater Horizon oil during its journey from the Mississippi Canyon block 252 (MC252) wellhead, first discussing the formation of the oil and gas plume and the ensuing oil droplet size distribution, then focusing on the behavior of the oil on the water surface with and without waves. It then reports on massive drifter experiments in the Gulf of Mexico and the impact of the Mississippi River on the oil transport. Finally, it concludes by addressing the formation of oil–particle aggregates. Although physical processes lend themselves to numerical modeling, we attempted to elucidate them without using advanced modeling, as our goal is to enhance communication among scientists, engineers, and other entities interested in oil spills.

Deepwater hydrocarbon releases experience complex chemical and physical processes. To assess simplifications of these processes on model predictions, we present a sensitivity analysis using simulations for the Deepwater Horizon oil spill. We compare the buoyant multiphase plume metrics (trap height, rise time etc), the hydrocarbon mass flowrates at the near-field plume termination and their mass fractions dissolved in the water column and reaching the water surface. The baseline simulation utilizes a 19-component hydrocarbon model, live-fluid state equations, hydrate dynamics, and heat and mass transfer. Other simulations turn-off each of these processes, with the simplest one using inert oil and methane gas. Plume metrics are the least sensitive to the modeled processes and can be matched by adjusting the release buoyancy flux. The mass flowrate metrics are more sensitive. Both liquid- and gas-phase mass transfer should be modeled for accurate tracking of soluble components (e.g. C

Physical transport processes such as the circulation and mixing of waters largely determine the spatial distribution of materials in the ocean. They also establish the physical environment within which biogeochemical and other processes transform materials, including naturally occurring nutrients and human-made contaminants that may sustain or harm the region’s living resources. Thus, understanding and modeling the transport and distribution of materials provides a crucial substrate for determining the effects of biological, geological, and chemical processes. The wide range of scales in which these physical processes operate includes microscale droplets and bubbles; small-scale turbulence in buoyant plumes and the near-surface “mixed” layer; submesoscale fronts, convergent and divergent flows, and small eddies; larger mesoscale quasi-geostrophic eddies; and the overall large-scale circulation of the Gulf of Mexico and its interaction with the Atlantic Ocean and the Caribbean Sea; along with air-sea interaction on longer timescales. The circulation and mixing processes that operate near the Gulf of Mexico coasts, where most human activities occur, are strongly affected by wind- and river-induced currents and are further modified by the area’s complex topography. Gulf of Mexico physical processes are also characterized by strong linkages between coastal/shelf and deeper offshore waters that determine connectivity to the basin’s interior. This physical connectivity influences the transport of materials among different coastal areas within the Gulf of Mexico and can extend to adjacent basins. Major advances enabled by the Gulf of Mexico Research Initiative in the observation, understanding, and modeling of all of these aspects of the Gulf’s physical environment are summarized in this article, and key priorities for future work are also identified.

The

We present an analysis of 2225 simulations of artificial oil well blowouts in nearshore and offshore waters of Newfoundland, Canada. In the simulations, we coupled the VDROP-J and TAMOC models to simulate the fate and transport of oil and gas from the release to the sea surface. Simulations were conducted with and without subsea dispersant injection. We analyzed the simulation database to quantify the mass fraction of oil and gas that surfaces, the mass fraction of released benzene that surfaces, and the horizontal offset to the surfacing zone. These data are also synthesized to yield empirical correlations to predict these output metrics from key input parameters. These correlations are summarized in an excel spreadsheet that allows rapid evaluation of spill dynamics with minimal initial knowledge of spill details. We call this tool an offshore response guidance table, which allows exploration of spill dynamics under diverse spill and response options.

Hurricane Harvey heavily impacted Texas in August 2017 due to an extreme amount of rainfall, especially in the large metropolitan area in and around Houston. There was an offshore storm surge associated with Harvey, and while it raised the water level in the bay, possibly prolonging flooding in the Houston area by slowing drainage, it was not responsible for flooding, as water flowed continuously out of the bay during peak flooding. Salinity measured near the mouth of the San Jacinto river dropped to 0 from 15 psu in 1.5 days after the start of storm-related outflow from the bay; the whole bay was fully freshened in 3.6 days. Depth-averaged outflow from the entrance channel reached 2 m/s. Using publicly available oceanographic data within Galveston Bay, we estimate the amount of freshwater that flowed into the bay from this rainfall to be 17 ± 5 km3 (14 million acre feet), or about 5 times the volume of Galveston Bay itself. This is less than, but close to, the freshwater input source: 20 km3 of rain that was estimated from Doppler radar to have accumulated in the drainage basins contributing to the bay. By comparison, the freshwater inflow estimates by the Texas Water Development Board (TWDB) predicts 13 km3 (11.5 million acre feet) of inflow to Galveston Bay during Hurricane Harvey.

Understanding the size of oil droplets released from a jet in crossflow is crucial for estimating the trajectory of hydrocarbons and the rates of oil biodegradation/dissolution in the water column. We present experimental results of an oil jet with a jet-to-crossflow velocity ratio of 9.3. The oil was released from a vertical pipe 25 mm in diameter with a Reynolds number of 25 000. We measured the size of oil droplets near the top and bottom boundaries of the plume using shadowgraph cameras and we also filmed the whole plume. In parallel, we developed a multifluid large eddy simulation model to simulate the plume and coupled it with our VDROP population balance model to compute the local droplet size. We accounted for the slip velocity of oil droplets in the momentum equation and in the volume fraction equation of oil through the local, mass-weighted average droplet rise velocity. The top and bottom boundaries of the plume were captured well in the simulation. Larger droplets shaped the upper boundary of the plume, and the mean droplet size increased with elevation across the plume, most likely due to the individual rise velocity of droplets. At the same elevation across the plume, the droplet size was smaller at the centre axis as compared with the side boundaries of the plume due to the formation of the counter-rotating vortex pair, which induced upward velocity at the centre axis and downward velocity near the sides of the plume.

In this paper we present an experimental and theoretical study of weak bubble plumes in unstratified and stationary water. We define a weak bubble plume as one that spreads slower than the linear rate of a classic plume. This work focuses on the characteristics of the mean flow in the plume, including centreline velocity, plume spreading and entrainment of ambient water. A new theory based on diffusive spreading instead of an entrainment hypothesis is used to describe the lateral spreading of the bubbles and the associated plume. The new theory is supported by the experimental data. With the measured data of liquid volume fluxes and the new theory, we conclude that the weak bubble plume is a decreasing entrainment process, with the entrainment coefficient $\unicode[STIX]{x1D6FC}$ in the weak bubble plume decreasing with height $z$, following $\unicode[STIX]{x1D6FC}\sim z^{-1/2}$, and taking on values much smaller than those in a classic bubble plume. An additional non-dimensional diffusion coefficient, $\hat{E_{t}}\sim E_{t}U_{s}^{2}/B_{0}$, is also needed to describe the evolution of the volume and kinematic momentum fluxes for the mean flow in the weak bubble plume. Here, $E_{t}$ is the effective turbulent diffusion coefficient, $U_{s}$ is the terminal rise velocity of the bubbles, and $B_{0}$ is the kinematic buoyancy flux of the source. Finally, we provide a unified framework for the mean flow characteristics, including volume flux, momentum flux and plume spreading for the classic and weak bubble plumes, which also provides insight on the transition from classic to weak bubble plume behaviour.

We present the turbulent kinetic energy (t.k.e.) budget of a dilute bubble plume in its asymptotic state. The budget is derived from an experimental dataset of bubble plumes formed inside an unstratified water tank. The experiments cover both the adjustment phase and asymptotic state of the plume. The diameters $d$ of air bubbles are in the range 1–4 mm and the air void fraction $\unicode[STIX]{x1D6FC}_{g}$ is between 0.7 % and 1.8 %. We measured the three components of the instantaneous liquid velocity vector with a profiling acoustic Doppler velocimeter. From the experiments, we found the following inside the heterogeneous bubble core of the plume: (i) the probability density functions of the standardized liquid fluctuations are very similar to those of homogeneous bubble swarms rising with and without background liquid turbulence; (ii) the characteristic temporal frequency $f_{cwi}$ at which bubbles inject t.k.e. into the liquid agrees with the prediction $f_{cwi}=0.14u_{s}/d$ observed and theoretically derived for homogeneous bubble swarms ($u_{s}$ is the bubble slip velocity); (iii) the liquid turbulence is anisotropic with the ratio of turbulence intensities between the vertical and horizontal components in the range 1.9–2.1; (iv) the t.k.e. production by air bubbles is much larger than that by liquid mean shear; and (v) an increasing fraction of the available work done by bubbles is deposited into liquid turbulence as one moves away from the plume centreline. Together with the existing knowledge of homogeneous bubble swarms, our results of the heterogeneous bubble plume support the view that millimetre-sized bubbles create specific patterns of liquid fluctuations that are insensitive to flow conditions and can therefore be possibly modelled by a universal form.

In this paper, we present the results of numerical simulations matched to laboratory experiments of tidal, starting-jet vortices forming at idealized, barotropic inlets. The laboratory experiments are for sinusoidally varying inflow/outflow along a wide, flat basin. Inlet configurations include simple inlets with negligible channel length as well as a longer inlet channels through a long barrier island and jettied inlet. Laboratory observations are made using particle image velocimetry, and we analyze the laboratory and numerical model velocity fields to compare starting-jet trajectory, diameter, and total circulation. The numerical simulations use the Fine Resolution Environmental Hydrodynamic model, solving the three-dimensional, hydrostatic, barotropic equations of motion. Our goal is to identify the minimum model attributes necessary to match the vortex properties. This is accomplished using a third-order upwind scheme for advection, a constant bottom friction drag coefficient, and a one-equation turbulence model for transport of turbulent kinetic energy. The optimal value of the bottom drag coefficient matches the time-average value at the basin inflow/outflow boundaries, and the optimal dissipation coefficient, $$C_{me}$$, was an order of magnitude smaller than literature values for a steady open-channel flow. We show that the drag coefficient mainly affects the advection speeds of the outer coastal waters, which control the penetration of the tidal vortices away from the inlet, and the lower turbulence dissipation rate results from the low turbulent dissipation in the large, shallow starting-jet vortices.

During undersea oil blowout in crossflow conditions, the oil droplets entrained horizontally which increased the residence time of droplets in the water column. Knowledge of the trajectory of an oil plume is important for predicting the pathways of hydrocarbons and to devise countermeasures. We conducted large-scale experiments in the Ohmsett tank where we released oil from a one-inch vertical orifice that was towed to produce the behavior of a jet in crossflow. The average oil velocity at the orifice was 1.36 m/s and the crossflow velocity was around 0.27 m/s which resulted in a jet-to-crossflow velocity ratio of 5.0. The results were simulated numerically using the Large Eddy Simulation (LES) turbulence model and the mixture multiphase model within the open-source software OpenFOAM. The instruments including ADVs, LISSTs, shadowgraph cameras, holographic camera, and fluorometers were employed. The oil jet released from the nozzle started to meander in the vertical direction most probably due to weak crossflow. The trajectory and meandering behavior of the oil jet, wavy pattern along the leading edge of the jet and column breakup observed in the experiments were captured well with the numerical simulation. The surface breakup just above the orifice created ligaments and droplets downstream of the jet. Larger oil droplets were observed near the upper boundary of the plume due to their higher buoyancy while the smaller droplets were suspended in the water column and they were entrained by water crossflow. This work reveals that different size of droplets determines the overall shape of plumes mostly the upper and lower boundaries of the plume.

We developed an integral plume model to simulate the behavior of bubble plumes generated from line-source geometry in stratified ambient reservoirs by adapting the double-plume integral mod...

Explaining the dynamics of gas-saturated live petroleum in deep water remains a challenge. Recently, Pesch et al. (Environ. Eng. Sci. 2018, 35, 289−299) reported laboratory experiments on methane-saturated oil droplets under emulated deep-water conditions, providing an opportunity to elucidate the underlying dynamical processes. We explain these observations with the Texas A&M Oil spill/Outfall Calculator (TAMOC), which models the pressure-, temperature-, and composition-dependent interactions between: oil-gas phase transfer; aqueous dissolution; and densities and volumes of liquid oil droplets, gas bubbles, and two-phase droplet-bubble pairs. TAMOC reveals that aqueous dissolution removed >95% of the methane from ~3.5-mm live oil droplets within 14.5 min, prior to gas bubble formation, during the experiments of Pesch et al. Additional simulations indicate that aqueous dissolution, fluid density changes, and gas-oil phase transitions (ebullition, condensation) may all contribute to the fates of live oil and gas in deep water, depending on the release conditions. Illustrative model scenarios suggest that 5-mm diameter gas bubbles released at

Exploring how the multiscale interaction between underwater oil and gas plumes and the environment impacts plume composition and trajectory.

Highlights • Pseudo-components for high-pressure deep-water oil spill models • Estimation of Peng-Robinson EOS parameters for distillation-cut pseudo-components • Modeling of the non-ideal chemistry of hydrocarbons in deep waters • New correlations to calculate chemical properties of petroleum fractions • Validated with 614 oils from the ADIOS oil library Abstract Deep-water oil spills represent a major, localized threat to marine ecosystems. Multi-purpose computer models have been developed to predict the fate of spilled oil. These models include databases of pseudo-components from distillation cut analysis for hundreds of oils, and have been used for guiding response action, damage assessment, and contingency planning for marine oil spills. However, these models are unable to simulate the details of deep-water, high-pressure chemistry. We present a new procedure to calculate the chemical properties necessary for such simulations that we validate with 614 oils from the ADIOS oil library. The calculated properties agree within 20.4% with average values obtained from data for measured compounds, for 90% of the chemical properties. This enables equation-of-state calculations of dead oil density, viscosity, and interfacial tension. This procedure enables development of comprehensive oil spill models to predict the behavior of petroleum fluids in the deep sea.

The BP-operated Deepwater Horizon (DWH) oil rig blowout in April 2010 led to the release of about 700,000 tons of crude oil and 250,000 tons of gas into the Gulf of Mexico (GoM) before it was capped. It also led, tragically, to 11 deaths and 16 injuries to people on the rig. This was the first deep, subsurface ocean spill in offshore oil exploration and posed many technical issues as a result. The GoM Research Initiative (GoMRI) was set up with funding provided by BP to improve the science for responding to future spills. Under GoMRI, the Gulf Integrated Spill Research (GISR) consortium was established to increase the understanding of how petroleum fluids in the ocean behave and improve the ability to predict what happens after a spill. GISR's aim was to construct a multiscale nested model suite that covers scales from droplets to an ocean basin, validated by field and laboratory experiments. Thus, we can follow an oil drop from its first release to its arrival on a shoreline, taking into account natural rates of mixing, dissolution, evaporation, and degradation. This was needed, because during the spill, available models all tended to operate at different scales but did not interact. There are also a number of shallow bays along the northern GoM that are of great importance to local fisheries, and these were not included in existing models.

This paper presents a set of stereoscopic particle image velocimetry (SPIV) measurements of a turbulent round water jet (jet exit Reynolds number $$Re = 2679$$ and turbulent Reynolds number $$Re_T = 113$$ ) discharged into an initially stationary ambient. The data were taken on the jet centerplane and at non-dimensional downstream distances $$x/D = 27{-}37$$ ( $$x =$$ axial coordinate and $$D =$$ orifice diameter), where the jet turbulence had evolved into a self-preserving state. Budgets of turbulent kinetic energy k and individual components of the Reynolds stress tensor $$R_{ij}$$ are extracted from the velocity measurements and compared to recent experimental data of an air jet ( $$x/D = 30, Re = 140{,}000$$ ) and direct numerical simulation data ( $$x/D = 15, Re = 2000$$ ). The comparison reveals that the datasets are consistent with each other but that the turbulent transport of energy $$\overline{u^2_i}$$ appears to differ between the present low-Re water jet and the high-Re air jet. Nonetheless, the non-dimensional profile of turbulent dissipation rate $${\overline{\epsilon }}$$ , obtained as the closing term (balance) of the k-budget, is very similar in all studies. The commonly used Lumley’s model for pressure–velocity correlation (pressure transport term in k-budget) is evaluated using the instantaneous pressure field computed from the time-resolved planar velocity data. We find that Lumley’s model is deficient in the jet core $$|r/b_g| < 0.3$$ ( $$r =$$ radial coordinate and $$b_g =$$ Guassian half-width), while performing adequately away from it. Finally, the present data are used to compute terms appearing in the exact transport equation of $${\overline{\epsilon }}$$ . Combining both the k and $${\overline{\epsilon }}$$ budgets, model coefficients in the commonly used two-equation $$k-{\overline{\epsilon }}$$ turbulence closure model are evaluated from the present data. If a fixed set of model coefficients is to be employed in a jet simulation, the following values of the model coefficients are recommended to optimize predictions for the mean flow field, for k, and for $${\overline{\epsilon }}$$ : $$C_{1\epsilon } = 1.2, C_{2\epsilon } = 1.6, C_{\mu } = 0.11, \sigma _k = 1.0$$ and $$\sigma _\epsilon = 1.3$$ .

Subsea oil well blowouts and pipeline leaks release oil and gas to the environment through vigorous jets. Predicting the breakup of the released fluids in oil droplets and gas bubbles is critical to predict the fate of petroleum compounds in the marine water column. To predict the gas bubble size in oil well blowouts and pipeline leaks, we observed and quantified the flow behavior and breakup process of gas for a wide range of orifice diameters and flow rates. Flow behavior at the orifice transitions from pulsing flow to continuous discharge as the jet crosses the sonic point. Breakup dynamics transition from laminar to turbulent at a critical value of the Weber number. Very strong pure gas jets and most gas/liquid co-flowing jets exhibit atomization breakup. Bubble sizes in the atomization regime scale with the jet-to-plume transition length scale and follow −3/5 power-law scaling for a mixture Weber number.

During the Deepwater Horizon disaster, a substantial fraction of the 600,000-900,000 tons of released petroleum liquid and natural gas became entrapped below the sea surface, but the quantity entrapped and the sequestration mechanisms have remained unclear. We modeled the buoyant jet of petroleum liquid droplets, gas bubbles, and entrained seawater, using 279 simulated chemical components, for a representative day (June 8, 2010) of the period after the sunken platform's riser pipe was pared at the wellhead (June 4-July 15). The model predicts that 27% of the released mass of petroleum fluids dissolved into the sea during ascent from the pared wellhead (1,505 m depth) to the sea surface, thereby matching observed volatile organic compound (VOC) emissions to the atmosphere. Based on combined results from model simulation and water column measurements, 24% of released petroleum fluid mass became channeled into a stable deep-water intrusion at 900- to 1,300-m depth, as aqueously dissolved compounds (∼23%) and suspended petroleum liquid microdroplets (∼0.8%). Dispersant injection at the wellhead decreased the median initial diameters of simulated petroleum liquid droplets and gas bubbles by 3.2-fold and 3.4-fold, respectively, which increased dissolution of ascending petroleum fluids by 25%. Faster dissolution increased the simulated flows of water-soluble compounds into biologically sparse deep water by 55%, while decreasing the flows of several harmful compounds into biologically rich surface water. Dispersant injection also decreased the simulated emissions of VOCs to the atmosphere by 28%, including a 2,000-fold decrease in emissions of benzene, which lowered health risks for response workers.

Hypolimnetic oxygenation is an increasingly common lake management strategy for mitigating hypoxia/anoxia and associated deleterious effects on water quality. A common effect of oxygenation is increased oxygen consumption in the hypolimnion and predicting the magnitude of this increase is the crux of effective oxygenation system design. Simultaneous measurements of sediment oxygen flux (JO2) and turbulence in the bottom boundary layer of two oxygenated lakes were used to investigate the impact of oxygenation on JO2. Oxygenation increased JO2 in both lakes by increasing the bulk oxygen concentration, which in turn steepens the diffusive gradient across the diffusive boundary layer. At high flow rates, the diffusive boundary layer thickness decreased as well. A transect along one of the lakes showed JO2 to be spatially quite variable, with near-field and far-field JO2 differing by a factor of 4. Using these in situ measurements, physical models of interfacial flux were compared to microprofile-derived JO2 to determine which models adequately predict JO2 in oxygenated lakes. Models based on friction velocity, turbulence dissipation rate, and the integral scale of turbulence agreed with microprofile-derived JO2 in both lakes. These models could potentially be used to predict oxygenation-induced oxygen flux and improve oxygenation system design methods for a broad range of reservoir systems.

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.

Laboratory studies of tidal vortex formation and propagation through an idealized inlet configuration are presented for various water depths over flat bathymetry. Using surface particle ima...

The science of deep oil spills is complex, spanning several engineering and scientific specialties, different environmental conditions, and a large range of dimensional scales. It is also an applied and pragmatic field where research is expected to produce a better assessment and improved response of any spill incident. This summary chapter reviews at an introductory level the important physical and chemical factors relevant to deep oil blowouts, beginning with the nature of the crude oil itself. While knowledge of the necessary properties of such a mixture of hydrocarbons is often limited, this chapter describes the information typically known to spill responders, expressed in units common to the industry. Material characteristics of the leaking reservoir are defined along with some special features of the subsurface release and plume that are not present in surface spills. Finally, the early far-field behavior of the submerged oil is described.

Deepwater spills pose a unique challenge for reliable predictions of oil transport and fate, since live oil spewing under very high hydrostatic pressure has characteristics remarkably distinct from oil spilling in shallow water. It is thus important to describe in detail the complex thermodynamic processes occurring in the near-field, meters above the wellhead, and the hydrodynamic processes in the far-field, up to kilometers away. However, these processes are typically modeled separately since they occur at different scales. Here we directly couple two oil prediction applications developed during the Deepwater Horizon blowout operating at different scales: the near-field Texas A&M Oilspill Calculator (TAMOC) and the far-field oil application of the Connectivity Modeling System (oil-CMS). To achieve this coupling, new oil-CMS modules were developed to read TAMOC output, which consists of the description of distinct oil droplet “types,” each of specific size and pseudo-component mixture that enters at a given mass flow rate, time, and position into the far field. These variables are transformed for use in the individual-based framework of CMS, where each droplet type fits into a droplet size distribution (DSD). Here we used 19 pseudo-components representing a large range of hydrocarbon compounds and their respective thermodynamic properties. Simulation results show that the dispersion pathway of the different droplet types varies significantly. Indeed, some droplet types remain suspended in the subsea over months, while others accumulate in the surface layers. In addition, the decay rate of oil pseudo-components significantly alters the dispersion, denoting the importance of more biodegradation and dissolution studies of chemically and naturally dispersed live oil at high pressure. This new modeling tool shows the potential for improved accuracy in predictions of oil partition in the water column and of advancing impact assessment and response during a deepwater spill.

Petroleum is one of the most complex naturally occurring organic mixtures. The physical and chemical properties of petroleum in a reservoir depend on its molecular composition and the reservoir conditions (temperature, pressure). The composition of petroleum varies greatly, ranging from the simplest gas (methane), condensates, conventional crude oil to heavy oil and oil sands bitumen with complex molecules having molecular weights in excess of 1000 daltons (Da). The distribution of petroleum constituents in a reservoir largely depends on source facies (original organic material buried), age (evolution of organisms), depositional environment (dysoxic versus anoxic), maturity of the source rock (kerogen) at time of expulsion, primary/secondary migration, and in-reservoir alteration such as biodegradation, gas washing, water washing, segregation, and/or mixing from different oil charges. These geochemical aspects define the physical characteristics of a petroleum in the reservoir, including its density and viscosity. When the petroleum is released from the reservoir through an oil exploration accident like in the case of the Deepwater Horizon event, several processes are affecting the physical and chemical properties of the petroleum from the well head into the deep sea. A better understanding of these properties is crucial for the development of near-field oil spill models, oil droplet and gas bubble calculations, and partitioning behavior of oil components in the water. Section 3.1 introduces general aspects of the origin of petroleum, the impact of geochemical processes on the composition of a petroleum, and some molecular compositional and physicochemical background information of the Macondo well oil. Section 3.2 gives an overview over experimental determination of all relevant physicochemical properties of petroleum, especially of petroleum under reservoir conditions. Based on the phase equilibrium modeling using equations of state (EOS), a number of these properties can be predicted which is presented in Sect. 3.3 along with a comparison to experimental data obtained with methods described in Sect. 3.2.

Highlights • Biodegradation is a critical process that governs the fate of oil spilled subsea. • Current models use first-order decay of pseudo-components of the oil composition. • We simulated subsea oil spills varying composition, biodegradation rates, and droplet size. • The most important parameter affecting surfacing time and location was droplet size. • The choice of biodegradation model and rates was of secondary importance. Abstract Biodegradation is important for the fate of oil spilled in marine environments, yet parameterization of biodegradation varies across oil spill models, which usually apply constant first-order decay rates to multiple pseudo-components describing an oil. To understand the influence of model parameterization on the fate of subsurface oil droplets, we reviewed existing algorithms and rates and conducted a model sensitivity study. Droplets were simulated from a blowout at 2000 m depth and were either treated with sub-surface dispersant injection (2% dispersant to oil ratio) or untreated. The most important factor affecting oil fate was the size of the droplets, with biodegradation contributing substantially to the fate of droplets ≤0.5 mm. Oil types, which were similar, had limited influence on simulated oil fate. Model results suggest that knowledge of droplet sizes and improved estimation of pseudo-component biodegradation rates and lag times would enhance prediction of the fate and transport of subsurface oil.

Mean flow and turbulence in bubble-in-chain induced flows are experimentally observed at various release frequencies and flow rates. We find that horizontal water velocity profiles collapse to a universal Gaussian distribution and one-dimensional velocity spectra to a consistent slope of \ensuremath{-}3.

Understanding the trajectory of oil droplets in crossflow jets is important to estimate the pathways of hydrocarbons and to plan countermeasures. We report experimental results of an oil jet with release velocity around 1.5 m/s in a crossflow of 0.3 m/s. The hydrodynamics of the jet obtained with the Large Eddy Simulation (LES) were used to predict the migration of the oil droplets. Two Lagrangian techniques were explored, one with the inertia of the droplet is considered and the other that treats the droplets as massless particles with rising velocities corresponding to their size. We did not note a large difference between the two approaches. The droplets showed stronger segregation in the vertical direction, which renders the usage of a Gaussian distribution approximation in the vertical inapplicable. The dispersion coefficient at each direction was computed for different-sized droplets. The eddy diffusivity computed based on Boussinesq gradient approximation using the LES data was compared with the dispersion coefficients obtained based on Lagrangian tracking. We also found that droplets 500 μ m and larger escape the vortex while smaller ones get trapped within the vortex. A similar outcome was observed using a vortex trapping function based on inward–outward force balancing at the elevation of the vortex core. The counter-rotating vortex pair (CVP) altered the distribution of droplets of 1 mm and smaller significantly, and bimodal concentration distributions with peaks near the CVP vortex cores and minimum concentration near the center plane were obtained in the lateral–horizontal​ direction. Therefore, measurements of the oil droplet size distribution (DSD) in the center plane of crossflow jets could underestimate the number of small droplets in the whole plume.

Characteristics of laboratory-scale bubble-driven buoyant plumes in a stably stratified quiescent fluid are studied using large-eddy simulation (LES). As a bubble plume entrains stratified ambient water, its net buoyancy decreases due to the increasing density difference between the entrained and ambient fluids. A large fraction of the entrained fluid eventually detrains and falls along an annular outer plume from a height of maximum rise (peel height) to a neutral buoyancy level (trap height), during which less buoyant scalars (e.g. small droplets) are trapped and dispersed horizontally, forming quasi-horizontal intrusion layers. The inner/outer double-plume structure and the peel/intrusion process are found to be more distinct for cases with small bubble rise velocity, while weak and unstable when the slip velocity is large. LES results are averaged to generate distributions of mean velocity and turbulent fluxes. These distributions provide data for assessing the performance of previously developed closures used in one-dimensional integral plume models. In particular, the various LES cases considered in this study yield consistent behaviour for the entrainment coefficients for various plume cases. Furthermore, a new continuous peeling model is derived based on the insights obtained from LES results. Comparing to previous peeling models, the new model behaves in a more self-consistent manner, and it is expected to provide more reliable performance when applied in integral plume models.

This paper reports the results of quantitative imaging using a stereoscopic, high-speed camera system at two natural gas seep sites in the northern Gulf of Mexico during the Gulf Integrated Spill Research G07 cruise in July 2014. The cruise was conducted on the E/V Nautilus using the ROV Hercules for in situ observation of the seeps as surrogates for the behavior of hydrocarbon bubbles in subsea blowouts. The seeps originated between 890 and 1190 m depth in Mississippi Canyon block 118 and Green Canyon block 600. The imaging system provided qualitative assessment of bubble behavior (e.g., breakup and coalescence) and verified the formation of clathrate hydrate skins on all bubbles above 1.3 m altitude. Quantitative image analysis yielded the bubble size distributions, rise velocity, total gas flux, and void fraction, with most measurements conducted from the seafloor to an altitude of 200 m. Bubble size distributions fit well to lognormal distributions, with median bubble sizes between 3 and 4.5 mm. Measurements of rise velocity fluctuated between two ranges: fast-rising bubbles following helical-type trajectories and bubbles rising about 40% slower following a zig-zag pattern. Rise speed was uncorrelated with hydrate formation, and bubbles following both speeds were observed at both sites. Ship-mounted multibeam sonar provided the flare rise heights, which corresponded closely with the boundary of the hydrate stability zone for the measured gas compositions. The evolution of bubble size with height agreed well with mass transfer rates predicted by equations for dirty bubbles.

An integrated observational field effort that makes simultaneous and collocated measurements of turbulence and fine-scale parameters has been conducted near the Deepwater Horizon oil spill site in the northern Gulf of Mexico (GOM). Full water column profiles are collected across the continental slope in July 2013. The observational results suggest that strong turbulence is patchy and mostly measured in the thermocline and deepwater when using the buoyancy Reynolds number, Re b =200 criterion, the boundary between weak and strong turbulence. Bottom enhanced turbulence is often seen on the continental slope. Using the ratio of the turbulent velocity scale and the oil droplets rising velocity, we develop criteria for when turbulence will dominate the movement of oil droplets and when turbulence can be ignored. Based on the data collected, for oil droplets with rising velocity greater than 6×10 −3 m s −1 , the turbulence effect can be ignored on the continental slope of the northern GOM. For oil droplets with rising speed less than 10 −4 m s −1 , their motions will be affected by the turbulent flow at all depths. For oil droplets with rising speed between 10 −4 and 6×10 −3 m s −1 , the role of turbulence will depend on the strength of the local turbulence and water stratification. We also relate turbulent velocity to the size and density of oil droplets by estimating the rising velocity of different size oil droplets due to balance between buoyancy and drag force. Droplet size and density difference are the two critical parameters in determining the role of turbulence.

Experimental results were presented for the release of diesel oil from a one-inch (2.5 cm) vertical pipe in a crossflow at 0.27 m/s. The ratio of jet velocity to crossflow speed was 5.0 and the Reynolds number based on jet velocity and pipe diameter was 7.1 × 10 3 . In the experiments, the plume shape was photographed, and the oil droplets were measured at two vertical locations on the center axis of the plume. Acoustic Doppler velocimetry (ADV) data was also obtained and compared to numerical predictions. The plume was simulated using large eddy simulation (LES), and the mixture multiphase model. The impact of the oil buoyancy was captured by adding a transport term to the volume fraction equation. Using the rise velocity based on d50 (volume-median) droplet size in the lower part of the plume allowed us to capture the lower boundary of the plume, but the estimated upper boundary of the plume penetrated less into the crossflow as compared to the experimental findings. However, using the rise velocity of the d50 at the upper part of the plume allowed one to estimate the upper boundary of the plume. As the droplets are too small to be resolved by the LES, we could not use a systematic approach to allow the multiphase plume to spread to mimic the observations. Based on the simulation results, the interaction between the jet and crossflow yielded small-sized flow structures near the upper boundary of the plume. The wake vortices initiated from the leeward side of the plume showed an alternating vorticity pattern in the wake. The shear layer vortices were induced by Kevin-Helmholtz instabilities mostly on the windward side of the plume. The formation of counter rotating vortex pair (CVP) altered greatly the hydrodynamics of the jet from that of a vertical jet to manifest flow reversals in all directions. The formation of CVP is likely to enhance the mixing of chemicals and droplets within the plume.

In operational oil spill modeling, hydrodynamic models often employ a coarse-resolution grid for computational efficiency. However, this practical grid resolution poorly resolves small-scale flow features, such as starting jet vortices (tidal eddies) that are common at the inlet of bar-built estuaries with narrow inlet channels, particularly where channel dredging and jetties have been employed to aid ship traffic. These eddies influence Lagrangian transport paths and hence the fate of an oil spill potentially entering or leaving an estuary. This research quantifies the effect of tidal eddies on the mixing process and effects at model scales relevant to the operational prediction of oil spills, using the Galveston Bay entrance channel as a study site. Model grid sensitivity was analyzed, yielding an adequate eddy solution at the horizontal grid size of ∼140 m. It is demonstrated that the SUNTANS model at a practical operational grid resolution (∼400 m) captures neither the eddies nor their effects on particle movement, despite showing a satisfactory prediction of net transport through the inlet. The need for subgrid eddy modeling is discussed, and an empirical approach is proposed that can improve oil spill predictions at operational grid resolution scales when results from a high-resolution model are available.

We present the development and validation of a numerical modeling suite for bubble and droplet dynamics of multiphase plumes in the environment. This modeling suite includes real-fluid equations of state, Lagrangian particle tracking, and two different integral plume models: an Eulerian model for a double-plume integral model in quiescent stratification and a Lagrangian integral model for multiphase plumes in stratified crossflows. Here, we report a particle tracking algorithm for dispersed-phase particles within the Lagrangian integral plume model and a comprehensive validation of the Lagrangian plume model for single- and multiphase buoyant jets. The model utilizes literature values for all entrainment and spreading coefficients and has one remaining calibration parameter $$ \kappa $$ , which reduces the buoyant force of dispersed phase particles as they approach the edge of a Lagrangian plume element, eventually separating from the plume as it bends over in a crossflow. We report the calibrated form $$ \kappa = [(b - r) / b]^4 $$ , where b is the plume half-width, and r is the distance of a particle from the plume centerline. We apply the validated modeling suite to simulate two test cases of a subsea oil well blowout in a stratification-dominated crossflow. These tests confirm that errors from overlapping plume elements in the Lagrangian integral model during intrusion formation for a weak crossflow are negligible for predicting intrusion depth and the fate of oil droplets in the plume. The Lagrangian integral model has the added advantages of being able to account for entrainment from an arbitrary crossflow, predict the intrusion of small gas bubbles and oil droplets when appropriate, and track the pathways of individual bubbles and droplets after they separate from the main plume or intrusion layer.

Knowledge of the droplet size distribution (DSD) from the Deepwater Horizon (DWH) blowout is an important step in predicting the fate and transport of the released oil. Due to the absence of measurements of the DSD from the DWH incident, we considered herein hypothetical scenarios of releases that explore the realistic parameter space using a thoroughly calibrated DSD model, VDROP-J, and we attempted to provide bounds on the range of droplet sizes from the DWH blowout within 200 m of the wellhead. The scenarios include conditions without and with the presence of dispersants, different dispersant treatment efficiencies, live oil and dead oil properties, and varying oil flow rate, gas flow rate, and orifice diameter. The results, especially for dispersant-treated oil, are very different from recent modeling studies in the literature.

Development, testing, and application of a deep-sea, high-speed, stereoscopic imaging system are presented. The new system is designed for field-ready deployment, focusing on measurement of the characteristics of natural seep bubbles and droplets with high-speed and high-resolution image capture. The stereo view configuration allows precise evaluation of the physical scale of the moving particles in image pairs. Two laboratory validation experiments (a continuous bubble chain and an airstone bubble plume) were carried out to test the calibration procedure, performance of image processing and bubble matching algorithms, three-dimensional viewing, and estimation of bubble size distribution and volumetric flow rate. The results showed that the stereo view was able to improve the individual bubble size measurement over the single-camera view by up to 90% in the two validation cases, with the single-camera being biased toward overestimation of the flow rate. We also present the first application of this imaging system in a study of natural gas seeps in the Gulf of Mexico. The high-speed images reveal the rigidity of the transparent bubble interface, indicating the presence of clathrate hydrate skins on the natural gas bubbles near the source (lowest measurement 1.3 m above the vent). We estimated the dominant bubble size at the seep site Sleeping Dragon in Mississippi Canyon block 118 to be in the range of 2–4 mm and the volumetric flow rate to be 0.2–0.3 L/min during our measurements from 17 to 21 July 2014.

Coastal wetlands are an important ecosystem in nearshore regions, but they are also significant in affecting the flow patterns within these areas. Wave-induced flow in wetlands has complex circulation characteristics because of the interaction between waves and plants, especially in discontinuous vegetation. Here, a numerical investigation is performed to analyze the wave-averaged flow in vegetated mound–channel systems. Different water levels, vegetated conditions, and mound configurations are studied with the COULWAVE (Cornell University Long and Intermediate Wave) Boussinesq model. Model simulations show rip currents in the mound–channel systems, whose strength varies with different mound separation distances. The relative influence of vegetation depends on both mound configuration and water level. Approximately a 15% change in significant wave height results as waves propagate over the vegetated mounds, while up to a 75% decrease in the mean shoreward flow speed through vegetation is observed. In addition, vegetation influences the spatial distribution of mean water level within the wetlands. Dimensional analysis shows that rip current strength and primary circulation size depend on mound spacing, water depth, wave height, and vegetation cover.

We compare oil spill model predictions for a prototype subsea blowout with and without subsea injection of chemical dispersants in deep and shallow water, for high and low gas–oil ratio, and in weak to strong crossflows. Model results are compared for initial oil droplet size distribution, the nearfield plume, and the farfield Lagrangian particle tracking stage of hydrocarbon transport. For the conditions tested (a blowout with oil flow rate of 20,000 bbl/d, about 1/3 of the Deepwater Horizon), the models predict the volume median droplet diameter at the source to range from 0.3 to 6 mm without dispersant and 0.01 to 0.8 mm with dispersant. This reduced droplet size owing to reduced interfacial tension results in a one to two order of magnitude increase in the downstream displacement of the initial oil surfacing zone and may lead to a significant fraction of the spilled oil not reaching the sea surface.

This paper presents laboratory experiments of wave-driven hydrodynamics in a three-dimensional laboratory model of constructed coastal wetlands. The simulated wetland plants were placed on the tops of conically-shaped mounds, such that the laboratory model was dynamically similar to marsh mounds constructed in Dalehite Cove in Galveston Bay, Texas. Three marsh mounds were placed in the three-dimensional wave basin of the Haynes Coastal Engineering Laboratory at Texas A&M University, with the center of the central wetland mound located in the center of the tank along a plane of symmetry in the alongshore direction. The experiments included two water depths, corresponding to emergent and submerged vegetation, and four wave conditions, typical of wind-driven waves and ocean swell. The wave conditions were designed so that the waves would break on the offshore slope of the wetland mounds, sending a strong swash current through the vegetated patches. Three different spacings between the wetland mounds were tested. To understand the effects of vegetation, all experiments were repeated with and without simulated plants. Measurements were made throughout the nearshore region surrounding the wetland mounds using a dense array of acoustic Doppler velocimeters and capacitance wave gauges. These data were analyzed to quantify the significant wave height, phase average wave field and phase lags, wave energy dissipation over the vegetated patches, mean surface water levels, and the near-bottom current field. The significant wave height and energy dissipation results demonstrated that the bathymetry is the dominant mechanism for wave attenuation for this design. The presence of plants primarily increases the rate of wave attenuation through the vegetation and causes a blockage effect on flow through the vegetation. The nearshore circulation is most evident in the water level and velocity data. In the narrowest mound spacing, flow is obstructed in the channel between mounds by the mound slope and forced over the wetlands. The close mound spacing also retains water in the nearshore, resulting in a large setup and lower flows through the channel. As the spacing increases, flow is less obstructed in the channel. This allows for more refraction of waves off the mounds and deflection of flow around the plant patches, yielding higher recirculating flow through the channel between mounds. An optimal balance of unobstructed flow in the channel, wave dissipation over the mounds, and modest setup in the nearshore results when the edge-to-edge plant spacing is equal to the mound base diameter.