Researchers combined detailed observations, laboratory experiments, and existing numerical models to develop the Texas A&M Oil Spill (Outflow) Calculator (TAMOC) and improve predictions of subsea oil and gas plume dynamics.
The severity of an oil spill’s impact depends on many factors, including the amount and source of oil, the oil’s physical properties, how and where the oil spill material moves, and actions taken by responders. For a deep-water blowout, particles dispersed by multiphase plumes of gas and oil may follow a path different than the plume centerline, which can complicate efforts to simulate rising plumes and predict how much and where oil spill material travels.
Study author Scott Socolofsky explained, “In the oceans, the water column is both density stratified and flowing. These conditions are difficult to study simultaneously in the laboratory. We developed a model that is similar in structure to existing models, but that includes dissolution, and rigorously validated the model to data from the literature and our own studies, including laboratory and field-scale measurements.”
The researchers created a modeling framework that includes modules for the dispersed-phase equations (the Discrete Particle Model), particle tracking (the Lagrangian Particle Model), a multiphase integral plume based on a double-plume model (the Stratified Plume Model), and a Lagrangian framework for a crossflow dominated plume (the Bent Plume Model).
The publicly available model, called the Texas A&M Oil Spill (Outflow) Calculator (TAMOC) model, includes oil dissolution, a key process during the Deepwater Horizon incident. The improved prediction models using TAMOC may play a critical role in assessing the pros and cons of response tactics in future spills.
“The main advances of our model are to include a rigorous oil chemistry model, which we published previously, and to describe a method to simulate the effects of ocean currents on subsea oil well blowouts,” explained Socolofsky. “Although other models also simulate currents, their methods have not been well described. Because our model is publicly available, we carefully describe all methods and provide the source code.”
The researchers published their findings in Environmental Fluid Mechanics: Integral models for bubble, droplet, and multiphase plume dynamics in stratification and crossflow.
The team applied the TAMOC suite to two test cases defined in a previous model inter-comparison study to demonstrate how the suite’s modules simulate deep-water oil releases, compare the Stratified Plume Model and Bent Plume Model modules, and compare the suite’s predictions to other models. The simplified intrusion dynamics of the bent plume model compared to the stratified plume model had a negligible impact on the suite’s ability to predict intrusion depth and droplet fate. The TAMOC suite’s usefulness was highlighted by its ability to account for entrainment from arbitrary crossflow, predict small gas bubble and oil droplet intrusion, and track individual bubble and droplet pathways after separating from the main plume or intrusion layer.
“We tested two of the main modeling approaches in the literature and make the case that the normal approach used in oil spill models is often correct, giving credence to the predictions of other oil spill models,” said Socolofsky.
The National Oceanographic and Atmospheric Administration (NOAA) is currently using the TAMOC suite in its oil spill model GNOME (General NOAA Operational Modeling Environment). “In GNOME, NOAA needs a model to simulate the plume stage of the underwater transport of oil, and they have decided to use our model for this purpose. Hence, this study carefully validates the primary model that will be used by NOAA to forecast future subsea oil spills,” explained Socolofsky. “With the TAMOC, we are able to demonstrate the best choices for a blowout model and help to improve model prediction. Better predictions will save resources during the next major subsea blowout by helping to direct the response.”
Government and industry adoption of the TAMOC model earned Socolofsky a Texas A&M University College of Engineering Research Impact Award this year. The team is now working with NOAA to predict what might happen for an accidental oil spill in the Arctic.
By Nilde Maggie Dannreuther and Stephanie Ellis, Gulf of Mexico Research Initiative (GoMRI)
The study’s authors are Anusha L. Dissanayake, Jonas Gros, and Scott A. Socolofsky.
This research was made possible in part by a grant from the Gulf of Mexico Research Initiative (GoMRI) to the Center for the Integrated Modeling and Analysis of Gulf Ecosystems II (C-IMAGE II). Other funding sources included the National Science Foundation (CBET Award Number 1034112) and the United States Department of Homeland Security through the Arctic Domain Awareness Center Grant Award Number 2014-ST-061-ML0002).
Data are publicly available through the Gulf of Mexico Research Initiative Information and Data Cooperative (GRIIDC) at doi:10.7266/N79C6VFF.
