Wednesday 20 September 2017

The Center for the Integrated Modeling and Analysis of the Gulf Ecosystem

A tale of two Gulf spills: A research consortium of 19 institutions from 5 countries studying the impacts of oil spills on the Gulf of Mexico.

 

During the Deepwater Horizon blowout, chemical dispersants were injected in the deep ocean for the first time in history. Typically used at the surface, dispersants reduce the oil droplet size resulting in faster biodegradation by marine microorganisms. But how these dispersants interacted with the oil billowing from the well head is the main question of Task 1. The goals of near- and far-field modeling are to

(1) generate an integrated fundamental model that can be applied to predict oil behavior during marine blowouts

(2) quantify the effect of dispersant injection, and

(3) identify ecosystem components interacting with sub-surface and sedimented oil.

Task 1 operates through collaboration with the University of Miami, Texas A&M University, the University of Western Austraila, and NHL University of Applied Science in the Netherlands.

Research Summary

During the Deepwater Horizon blowout, chemical dispersants were injected in the deep ocean for the first time in history. Typically used at the surface, dispersants reduce the oil droplet size resulting in faster biodegradation by marine microorganisms. But how these dispersants interacted with the oil billowing from the well head is the main question of Task 1. The goals of near- and far-field modeling is to (1) generate an integrated fundamental model that can be applied to predict oil behavior during marine blowouts, (2) quantify the effect of dispersant injection, and (3) identify ecosystem components interacting with sub-surface and sedimented oil. Near-field dispersion refers to a mixture of oil and gas hydrates ascending soon after exiting the well. As this plume ascends in the water column the gasses dissolve and oil droplets remain. Tracking of these droplets is refered to as far-field modeling. Task 1 operates through collaboration with the University of Miami, Texas A&M University, the University of Western Austraila, and NHL University of Applied Science in the Netherlands.

Research Objectives

The goal of these near-field plume models is to accurately and efficiently predict the partitioning of oil and gas throughout the water column and at the sea surface. To achieve this goal the models must account for the currents, density stratification of the ambient seawater, supplied by the C-IMAGE physical models, and the partitioning and dissolution of oil and gas into the water column.

For this study we use the validated near-field Stratified Multiphase Integral Plume (SMIP) model (Socolofsky and Bhaumik, 2008; Socolofsky et al., 2011) that incorporates refined algorithms for stratification and cross-flow and predicts the partitioning of oil and gas throughout the water column and in the surface. More accurate multi-phase plume modeling requires improved knowledge of the initial conditions of the plume, gas-oil peeling processes, bubble/droplet size distribution, hydrate formation, and dissolution process for the bubbles and droplets. The accompanying plan to conduct high-pressure experimental research will provide insight on these important initial conditions. There is a critical need to enhance deep-water blowout models with stratification algorithms similar to the double-plume models developed by Crounse et al., (2007) and Socolofsky et al., (2008). Validation of the model focus on hindcasting the DWH release. The models are also used to forecast near-field plume behavior and the partitioning and water column distribution of oil and gas for a deep-water blowout scenario with varying compositions of petroleum.

To improve far-field model estimates of the chemical evolution, fate and transport of oil and gas from deep blowouts it is necessary to simultaneously account for key processes regulating:
(1) the formation of the rising plume in the near-field;
(2) the composition, distribution and fate of the sub-surface oil;
(3) and the dispersion, degradation and ecotoxicology of surface oil in the far-field.

The proposed suite of C-IMAGE nested circulation models in a single application is critical to identify pathways of the oil mixture from the deeper part of the GOM to the shallow coastal areas. This requires state-of-the-art computing techniques and the use of integrated oil spill application recently developed in the Connectivity Modeling System (CMS). The model represents discharged oil as droplets of varying sizes with distinct chemical fractions. In three-dimensional form, it predicted the dispersion and fate of the DWH releases over a few months, based on a preliminary assumed quantitative understanding of oil dispersion and degradation within 3D currents and mixing parameters.

Current Projects

Texas A&M Oil Spill Calculator – Socolofsky – Texas A&M University

The Texas A&M Oil Spill Calculator (TAMOC) models near-field plumes and computes transport of single droplets and simulates the development of subsurface intrusions and estimation of initial droplet size distributions in the near-field. 

Connectivity Modeling System – Paris – University of Miami

The Connectivity Modeling System (CMS) models the transport of droplets in the far-field using Lagrangian models to identify important parameters and processes involved in dispersion and fate. Incorporates biodegradation, droplet dynamics, MOSSFA formation, and icthyoplankton impacts.and plume experiments from task 2. 

Deepwater Horizon Hindcast Model – Coupled Near- and Far-field Components

Compiling surface distributions, sediment contamination, droplet size distribution, and ocean circulation creates a 4-dimensional visualization of the Deepwater Horizon spill. Outputs of the model include estimate subsurface distribution, PAH concentrations in water and sediments, and mass balance. Incorporates biodegradation, droplet dynamics, MOSSFA formation, icthyoplankton impacts, and Lagrangian dynamics from other C-IMAGE and GoMRI research projects.

Sapphire Autoclave – Aman – University of West Australia

High-pressure sapphire autoclave measures oil-in-water droplet size distributions (DSD) with variable oil thermophysical properties, presence of dispersants, and variable mixing length scale.

Hydrate film growth and oil viscosity are analyzed with the Sapphire Autoclave testing variable oil types and the addition of ionic and non-ionic dispersants.

Oil Entrainment Properties – Zienstra-Helfrich – NHL University of Applied Sciences

Entrainment of oil and the breakup into droplets are separate processes governed by separate parameters that can and should be included in spilled oil fate modelling.

 

Task 1 Publications

How oil properties and layer thickness determine the entrainment of spilled surface oil

How oil properties and layer thickness determ…

This study confirms that the entrainment of oil and the breakup into droplets are sep...

07-13-2016

Large-eddy simulation and parameterization of buoyant plume dynamics in stratified flow

Large-eddy simulation and parameterization of…

Abstract: Characteristics of laboratory-scale bubble-driven buoyant plumes in a stab...

05-23-2016

The NET effect of dispersants — a critical review of testing and modelling of surface oil dispersion

The NET effect of dispersants — a critical re…

Application of chemical dispersants or mechanical dispersion on surface oil is a trad...

11-24-2015

Ocean currents generate large footprints in marine palaeoclimate proxies

Ocean currents generate large footprints in m…

Fossils of marine microorganisms such as planktic foraminifera are among the cornerst...

11-24-2015

Quantification of the effect of oil layer thickness on entrainment of surface oil

Quantification of the effect of oil layer thi…

This study quantifies the effect of oil layer thickness on entrainment and dispersion...

11-24-2015

Texas A&M Oilspill Calculator (TAMOC): Modeling Suite for Subsea Spills

Texas A&M Oilspill Calculator (TAMOC): Mo…

The Texas A&M Oilspill Calculator (TAMOC) is a new, freely available modeling sui...

07-15-2015

Simulating the effects of droplet size, biodegradation and flow rate on the subsea evolution of deep plumes from the Macondo blowout

Simulating the effects of droplet size, biode…

The relative effects of hydrodynamic, thermodynamic, and geochemical factors on the f...

07-08-2015

C-IMAGE Researchers Turn the Pressure on SubSea Mechanics of Deep-Ocean Blowouts

C-IMAGE Researchers Turn the Pressure on SubS…

High-pressure visual experimental studies of oil-in-water dispersion droplet size In...

06-24-2015

Models for deep sea application of chemical dispersants

Models for deep sea application of chemical d…

A new study that explores various models of oil spill and dispersant projections has ...

06-12-2015

Factors that effect deep plume evolution

Factors that effect deep plume evolution

Simulating the effects of droplet size, high pressure biodegradation, and variable fl...

06-27-2014

How did dispersants impact subsea oil transport?

How did dispersants impact subsea oil transpo…

Evolution of the Macondo Well Blowout: Simulating the Effects of the Circulation and ...

06-26-2014

Reference for Connectivity Modeling System (C…

Connectivity Modeling System: A probabilistic modeling tool for the multi-scale track...

06-26-2014

Movement of the DwH Oil Spill Patch

Movement of the DwH Oil Spill Patch

Surface Evolution of the Deepwater Horizon Oil Spill Patch: Combined Effects of Circu...

06-25-2014

Response to Comment on "Evolution of the Macondo Well Blowout"

Response to Comment on "Evolution of the…

Response to Comment on "Evolution of the Macondo Well Blowout: Simulating the Effects...

06-25-2014

Listen to our Podcasts

  • #10 The Risks for Fish +

    #10 The Risks for Fish What happened to the fish in the days and weeks after the Deepwater Horizon oil spill? With a suite of Read More
  • #9 Forensic Oceanography +

    Listen to learn how scientists reanalyzed remotely sensed data taken in the late 1970s to study the Ixtoc 1 oil Read More
  • #8 In the Mud in Mexico +

    #8 In the Mud in Mexico “We were of the mind that with studying the Deepwater Horizon in the northern Gulf we weren’t getting a full Read More
  • #7 The Ixtoc Spill: Reflections +

    #7 The Ixtoc Spill: Reflections The Deepwater Horizon oil spill happened just a few years ago, but it might be possible to predict its impact Read More
  • #1 Overview of C-IMAGE +

    #1 Overview of C-IMAGE C-IMAGE PI Dr. Steven Murawski talks to David Levin about the research goals of our center and the importance of Read More
  • #2 Sampling for oil in the sediments in the Gulf of Mexico +

    #2 Sampling for oil in the sediments in the Gulf of Mexico C-IMAGE PI's Steven Murawski and David Hollander on board the Weatherbird II in August of 2012 talking to David Levin Read More
  • #3 The "not-so-visible" impacts of the Deepwater Horizon oil spill on the Gulf of Mexico +

    #3 The Three years after the BP oil well disaster, scientists are struggling to understand the effects on the Gulf ecosystem. From Read More
  • #4 Fitting the Gulf of Mexico inside a computer: how to build an ecosystem model +

    #4 Fitting the Gulf of Mexico inside a computer: how to build an ecosystem model Mind Open Media's David Levin talks with C-IMAGE members Cameron Ainsworth, Jason Lenes, Michelle Masi and Brian Smith about building Read More
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