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Decision Making Support Tools

Examination of Physical and Chemical Characteristics of Dielectric Fluids

The project consists of the chemical analysis and evaluation of the physical and behavioral properties of representative samples of three dielectric fluids. The fluids include synthetic ester based, natural ester based, and petroleum/mineral oil based fluids. An additional sample of a used/spent dielectric fluids will also be analyzed, if able to be located and acquired. This analysis will be used by spill response personnel and will help augment the NOAA Oil database.

Surface Water Droplet Size Distribution (DSD) Instruments: Laboratory Validation, Tank Deployment, and Field Evaluation

BSEE Response Research Branch is undertaking the DSD Instrument Evaluation project to better understand how surface water dispersant monitoring, as specified by the NCP SubPart J Monitoring Rule, can be practically implemented with existing technology, with specific emphasis on detection of oil and dispersed oil droplets in depths of 1 to 5 meters. The three main objectives of this project are:

Research to Support Analysis of Oil Spill Response Plans for Spills on Snow and Solid Ice

This project developed the ROSI calculator tool to facilitate assessment of an operator's oil spill response plan for a well blowout, tank failure, pipeline leak, or other spill that occurs during winter months and results in recovery operations on snow and solid ice using "yellow gear" equipment as described in the Alaska Clean Seas (ACS) Tactics Manual. Further, it asssed whether further research was recommended to verify and potentially update the formulas incorporated into the calculator tool.

LiDAR Oil Characterization and Automated Software Development

Under OSRR Project 1091, the NRL performed preliminary experiments to assess pulsed laser light technology (Light Detection And Ranging - LiDAR) ability to detect oil and characterize oil thickness on water. Initial testing conducted at Ohmsett demonstrated the successful application of LiDAR remote sensing to detect and measure the presence of oil at the surface and underwater.

This project will continue the development of the LiDAR system's ability to detect and characterize oil on the surface and varying subsurface layers thickness values and depth in the water.

Oil spill detection under ice and on seafloor

Although remote sensing technologies have been advanced for airborne and spaceborne sensors, it is still challenging to detect oil under/encapsulated in ice as well as on seafloor.

The objectives of this project are to:

Investigate and advance the current underwater technology to detect and measure thickness of oil under ice, encapsulated in ice and/or on the seafloor
Conduct testing at Ohmsett or CRREL to characterize the sensitivity of remote sensors for detecting and characterizing oil under ice, encapsulated in ice, and/or oil on the tank floor.

Advancement of MARINE SCOUT

Under Interagency Agreement (IAA) E13PG00031, the Bureau of Safety and Environmental Enforcement (BSEE)/U.S. Army Night Vision team completed a program that demonstrated a compact, lightweight, multi-spectral airborne sensor payload capable of detecting the presence of oil on water, distinguishing oil from false alarms such as kelp forests, and providing a reliable estimate of the thickness of the oil present on the water.

OIL DETECTION AND THICKNESS ESTIMATION UNDER/IN ICE BASED ON ELECTRICAL CAPACITANCE TOMOGRAPHY (ECT)

This project tested the Electrical Capacitance Tomography (ECT) sensor to detect oil in/under ice. For oil detection and thickness estimation under/in ice, where the access to the imaged region is limited to above its surface, the project team used a planar sensor design where the electrodes are mounted on a single plane and placed at a relatively close distance above the ice surface. 

The Web based General NOAA Oil Modeling Environment (WebGNOME) Anywhere

The current NOAA's WebGNOME platform displays the modeling bounds with available operational forecast models for selected areas. These areas are typically in shoreline areas. This project will expand the availability of forecast models to cover offshore areas where BSEE's regulated facilities reside. This added feature will enable the ability to run WebGNOME more easily, using available operational forecast models.

Slick Thickness Characterization Based on Low Noise, Polarized Synthetic Aperture Radar

The project team will use radar technology instead of optical or infrared methods in order to enable 24-hour, weather independent operation that can be deployed in inclement or difficult to access environments, and reduce dependence upon on-site personnel. The team will evaluate the capability of low noise L-band (1.26 GHz) synthetic aperture radar (SAR) imagery acquired by the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) sensor.
 

Shoreline Oil Spill Response Gaps and Opportunities Workshop

A workshop is being developed to discuss impacts of oil spills on shorelines. The workshop will bring together Subject Matter Experts (SME) from the spill response community, academia, and industry for the exchange of ideas and the exploration of the current state of the science of oil spill research. Traditional oil and gas exploration and production (E&P) as well as renewable energy (RE) will be explored. The results of this workshop will help guide BSEE Oil Spill Response Research (OSRR) to develop relevant Research and Technologies (R&T) in fulfillment of BSEE's mission.

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