To main content

Next Generation Oil Spill Contingency and Response Modelling and Integrated Results for Decision Making and Common Operating Picture

Next Generation Oil Spill Contingency and Response Modelling and Integrated Results for Decision Making and Common Operating Picture

Category
Conference lecture and academic presentation
Abstract
The Deepwater Horizon accident in 2010 turned the focus in oil spill research towards the subsea aspects of an oil spill and on how to respond to it. Blowout modelling, gas-oil-ratios (GOR) and droplet size distributions where studied with respect to their importance for the fate and behavior of the spilled oil, which consequently will determine environmental impact by short- and long-term effects. Availability of different response options like in-situ burning, subsea dispersant injection, mechanical subsea dispersion vs. mechanical recovery and containment, increased the demands for NEBA analyses where different (combinations) of response strategies and their outcome are assessed with respect to environmental and economic resources and the expected impact on these. Oil Spill Transport, Fate and Effects Models will have to implement new and update existing processes in order to deliver the required information to decision makers. Next generation models will implement newest research results while at the same integrate with solutions for decision making, incident management, common operating picture, risk assessment and contingency planning. We will present this by the example of SINTEF's OSCAR model which is currently under development for next generation model requirements. Research results from API, IOGP and GOMRI funded projects for oil spill response are combined with targeted post-processing tools and facilitate informed decision making in oil spill situations.
Language
English
Affiliation
  • SINTEF Ocean / Miljø og nye ressurser
Presented at
2016 Gulf of Mexico Oil Spill and Ecosystem Science Conference
Place
Tampa, Florida
Date
31.01.2016 - 03.02.2016
Organizer
Gulf of Mexico Research Initiative
Year
2016