GOM OI 2017-04-25 Oil Class V2 6000 - 125207 UTC

These data were collected as part of the National Oceanic and Atmospheric’s (NOAA) DWH Lessons Learned Studies: Detection of Oil Thickness and Emulsion Mixtures using Remote Sensing Platforms study on methods to estimate oil slick coverage and thickness. The Team developed methods for synoptic collection of satellite imagery, airborne imagery, surface oil characterization, oil and water chemistry, and subsurface oil slick data at both the Oil and Hazardous Materials Simulated Environmental Test Tank (Ohmsett) and the Mississippi Canyon lease block #20 (MC20), which has experienced an ongoing chronic oil discharge since 2004. Data shown here in NOAA’s Environmental Response Management Applications (ERMA) are part of the MC20 field research undertaken in 2016, 2017, and 2018. This research was primarily funded by the U.S. Department of the Interior, the Bureau of Safety and Environmental Enforcement (BSEE), and the Oil Spill Preparedness Division through Interagency Agreement E16PG00023 with the U.S. Department of Commerce, NOAA.

The primary objective of this research was to compare the ability of multiple remote sensing platforms to detect and quantify surface oil, and verify that anomalies identified in remote sensing images corresponded with oil slick features that could be observed and quantified in situ. This research was organized into 3 phases:

Phase 1: Characterized the detection of known oil thicknesses and oil-emulsions in a controlled environment, by performing multiple tests and calibrations for thermal, optical, and microwave sensors at the National Oil Spill Response Research & Renewable Energy Test Facility (Ohmsett) which is located at the Naval Weapons Station Earle Waterfront in Leonardo, New Jersey. Controlled experiments took place during July 2016.

Phase 2: Measured the open water oil thicknesses and oil-emulsions at the damaged Taylor Energy well field surface oiling site (MC20) by performing multiple tests and calibrations for thermal, optical and microwave sensors. Data were collected in November 2016, April 2017, and August 2017.

Phase 3: Developed operational methods and procedures for processing and interpreting each of the sensors products used during the experiments for future emergency operations.

The objective of synoptic sampling at MC20 was to provide data and observations on the water that verified (ground-truth) remote sensing data. The Team attempted to collect as much multi-platform and sensor data as was practicable while scheduling field sampling events to coincide with satellite collections. The Team also collected imagery from Unmanned Aerial Systems (UAS) and as many as four separate fixed-wing aircraft timed to these collections. These data were collected by multiple researchers from NOAA, Ocean Imaging Corp., Water Mapping LLC, University of North Texas (UNT), EPA, WHOI, Fototerra Aerial Survey LLC, and others. A total of 5 different data types are shown here in ERMA: in situ sampling, ship/flight trackline and photos, imagery, oil characterization, and oil on water samples. Summaries of the data collection methods are included below.

Ocean Imaging built a spectral library of oil thicknesses and emulsions in the visible and thermal IR data based on the Ohmsett tank tests. Ocean Imaging then compared the open water remote sensing data to data collected in the tank, including oil thickness, water:oil ratio, tank water temperature, oil and water spectroscopy, and photographs. Ocean Imaging ultimately classified oil thicknesses and emulsions based primarily on the red and thermal IR bands.Ocean Imaging also used supplemental satellite imagery from NOAA to help identify and classify oil slicks in their data.

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