During five years, in the frame of the NAOMI (New Advanced Observation Method Integration) research project, Total and ONERA have worked on radar and optical imagery to detect, characterize and quantify slicks at sea. Laboratory and pool measurements, physical modelling and offshore experiments have been combined to fully understand the signal collected over slick-covered area. As the measured signal is analytically expressed according to the geophysical parameters of the imaged slick, it enables to fully monitor the ocean surface: is a slick present? What kind of slick is it (extremely thin or not)? Is it a known product (existing in the data base)? Can the thickness be probed by the used of optical or radar device? What is the slick volume? In the Health Security and Environment (HSE) context, an exhaustive measurement campaign can be done in order to create a data base with hydrocarbon or hydrocarbon emulsion signatures, extinction coefficients, skin depths, minimum thicknesses perceptible thanks to extinction and thickness values. Thus, it offers more processing options in the optic branch of the tool to monitor the slick. Depending on the available data, optical and/or radar imagery, the capability of slick detection, characterization and quantification will be presented. After a recall of the HSE specificity, the paper will give an overview of the main features of the input data that is to say SAR and optical images. Then, based on modelling results, the optimal observation conditions for radar and optical imagery will be introduced. Afterwards, capability of detection will be described and illustrated for both the radar and the optical case. In the optical domain, the process will distinguish at least two classes: thin and thick. In the HSE context, a database can be used to identify some detected products. The last step is quantification. A sophisticated method, relying on L band radar imagery, will be used to identify pixels covered by a film, meaning presence of oil at the surface, and the ones for which the oil may be as droplets in the volume. The traditional use of SAR data is also extended to the estimation of the oil concentration within an oil and seawater mixture. For optical data, the most direct quantification process relies on automatic Bonn code classification. The code links a class with a range of thickness and computes a minimum and a maximum volume of product in each class. If the product is in the data base a more suited classification and volume assessment can be done. If the thickness is too thin (spectral signature due to absorption is too weak) or too thick (only the upper part of the product layer contributes to the signal), a thickness estimated thanks to pool experiment is associated to each class enabling to compute a volume per class and a global volume. In the other cases, in a near future, modelling would enable to assess the thickness. Concerning hydrocarbon emulsions, modelling in the optical domain is in progress in order to predict skin depth and to derive water content.
Going on toward the objectives of NAOMI (New Advanced Observation Method Integration) research project, Total and ONERA are working on hyperspectral imagery to detect, characterize and quantify spills at sea. An important part of this work consists in building a database of oil and water-in-oil emulsion reflectance. This database of spectral signatures will be used to analyze the properties of a slick thanks to hyperspectral imagery in the VNIR+SWIR domain and spectral matching techniques. The characterization of the hydrocarbons performed first in laboratory has been completed with a pool experiment. The aim of such an experiment is to measure more realistic spectral signatures in term of background and thickness than in laboratory. Starting from the sample of the emulsion released at sea during NOFO 2015 experiment, emulsion has been remixed once for laboratory measurements and second for the pool experiment. Indeed, its reflectance was measured in the laboratory but for a quite large thickness and it was difficult to predict how the thickness would be once the emulsion freely spread at the water surface. Moreover, depending on the thickness, a signature mixing emulsion and water background could be obtained. In such case, the signatures measured in the lab and in the pool may differ significantly. As a consequence, the use of spectral signature measured in laboratory may give poor spectral matching results. In order to get the answers, a pool experiment, piloted by ONERA in the frame of the NAOMI collaboration with TOTAL, was organized at CEDRE in Brest (France). CEDRE’s pool is usually used for oil recovery equipment testing or people operating such equipment training. Thus, the pool is large (1900 m²), fairly deep (3 m) and filled with ocean water. Known volumes of several products, including the NOFO 2015 emulsion, were successively poured into a delimited area within the pool. Two hyperspectral cameras put on board a cherry picker located on the pool quay were lifted at about 15 m above the delimited area in order to take images of each small spill. The obtained spectral signatures have been compared with the laboratory ones. Detection algorithms have been applied to the pool hypercubes in order to identify the pixels covered by the NOFO 2015 emulsion and a thickness assessment has been performed. A wide characterization of the NOFO2015 emulsion has been done thanks to laboratory measurements, in pool experiment and airborne images from the NOFO campaign in 2015. The paper will present the pool experiment and the corresponding image processing. A quick recall of the laboratory measurements will be done before presenting the pool and laboratory spectral signatures comparison. Then the spectral signatures will be compared with data from an airborne image of the 2015 NOFO campaign. Finally, a conclusion will be drawn concerning the information that can be extracted from hyperspectral airborne imagery for such kind of emulsion and more generally.