Project Page

Inferential/Parametric Forecasting of Subsurface Oil Trajectory Integrating Limited Reconnaissance Data with Flow Field Information for Emergency Response

Implementing Organization

Hohai University

Overview

DWH Project Funding

$900,821

Known Leveraged Funding

$0

Funding Organization

Gulf of Mexico Research Initiative (GoMRI)

Funding Program

Gulf of Mexico Research Initiative (GoMRI) Grant Program

Details

Project Category

Science

Project Actions

Physical Aspects Research

Targeted Resources

Petroleum

Project Description

When an oil spill or blowout occurs, immediate and pressing questions emerge as to where and when to dispatch response operations. Such questions become daunting when there is significant sunken (bottom) or submerged (water column) oil present, due either to intrinsically-high oil density, sediment entrainment/marine snow formation, and/or weathering. Side-scan sonar equipment is now available for rapid collection of approximate narrow-field data on bottom oil following a spill. While available models are not generally able to use such data directly and rapidly, the inferential SOSim model developed by the PIs group in 2010 can infer and project oil location in time based on limited field data. However, SOSim is designed for assessment only of sunken oil on bay bottoms and continental shelves from instantaneous spills. We propose to expand SOSim capability to allow tracking of submerged, water-column oil, and oil released continuously over a period of time, from available 2-D and 3-D field data, and demonstrate it versus field data from the Gulf of Mexico and elsewhere. Objectives are to: develop capability for modeling continuous spills and blowouts; develop capability for 3-D modeling; and integrate with an existing parametric model to develop inferential/parametric capability, with uncertainty bounds, exploiting reconnaissance data with flow field and bathymetry information.

Contact

James Englehardt
None
jenglehardt@miami.edu
Project Website
Project Partners

None

Affiliated Institutions

None

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