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Remote sensing for the oil in ice joint industry program 2007-2009
Abstract
This paper summarizes the different Oil in Ice Joint Industry Program (JIP) remote sensing activities carried out from 2007 to 2009, including: technology review and selection, airborne systems, Synthetic Aperture Radar (SAR) satellite imagery, trained dogs, and airborne Ground Penetrating Radar (GPR). A key finding is that flexible combinations of sensors operating from a variety of platforms are required to cover a range of oil in ice scenarios. Based on a combination of field data collected during the JIP and knowledge of sensor capabilities demonstrated in previous open water spills, the project concluded that the most useful remote sensing systems for spills in ice are expected to be: Forward Looking Infrared (FLIR) for oil on the surface in a broad range of ice concentrations, Side-Looking Airborne Radar (SLAR) and/or SAR for slicks on the water in very open ice covers, trained dogs on solid ice, and GPR for oil under snow or trapped in the ice. Detecting isolated oil patches among closely packed floes (>6/10) is a major challenge with any current remote sensing system, especially during periods of darkness, low clouds or fog. The most effective solution to this problem is to deploy closely spaced GPS tracking buoys to follow the ice and the oil. Arctic spill contingency plans need to account for the operational constraints of: aircraft and helicopter endurance, weather, and the potential for competing demands on limited remote sensing resources.
... The presence of sea ice causes severe harm to oil production and transportation, including damage to passing ships, oil platforms, and oil pipelines, which often leads to oil spills [2]. The opening of the Arctic route, resource development, and the rise in the number of naval vessels in the ice areas in the North China Sea have certainly increased the possibility of oil spills in the sea ice area [3][4][5]. These activities have increasingly become the focus of maritime and marine regulatory authorities [6]. ...
... In one study, researchers conducted laboratory and field trials in the Beaufort Sea in Northern Canada to test a variety of sensors and technologies [12]. Researchers in Canada and Norway have also started exploring the availability of a new generation of ground-penetrating radar, sonar, and methane detectors [4]. ExxonMobil has begun experimenting with nuclear magnetic resonance-based airborne detection systems [13]. ...
Researchers have studied oil spills in open waters using remote sensors, but few have focused on extracting reflectance features of oil pollution on sea ice. An experiment was conducted on natural sea ice in Bohai Bay, China, to obtain the spectral reflectance of oil-contaminated sea ice. The spectral absorption index (SAI), spectral peak height (SPH), and wavelet detail coefficient (DWT d5) were calculated using stepwise multiple linear regression. The reflectances of some false targets were measured and analysed. The simulated false targets were sediment, iron ore fines, coal dust, and the melt pool. The measured reflectances were resampled using five common sensors (GF-2, Landsat8-OLI, Sentinel3-OLCI, MODIS, and AVIRIS). Some significant spectral features could discriminate between oil-polluted and clean sea ice. The indices correlated well with the oil area fractions. All of the adjusted R2 values exceeded 0.9. The SPH model1, based on spectral features at 507–670 and 1627–1746 nm, displayed the best fitting. The resampled data indicated that these multi-spectral and hyper-spectral sensors could be used to detect crude oil on the sea ice if the effect of noise and spatial resolution are neglected. The spectral features and their identified changes may provide reference on sensor design and band selection.
... Based on experimental and measured data, Asihen et al. [14] demonstrated that the backscattering effects of C-band radar can effectively identify the differential characteristics of CSI and OCSI, facilitating the identification of oil spills on sea ice surfaces. Dickins et al. [15] conducted a series of experiments to test the capabilities of some remote sensing methods in detecting oil spills in IISWs. They tested SAR, infrared, VNIR, and laser fluorescence sensors. ...
Remote sensing has been widely used for oil spill monitoring in open waters. However, research on remote sensing monitoring of oil spills in ice-infested sea waters (IISWs) is still scarce. The spectral characteristics of oil-contaminated sea ice (OCSI) and clean sea ice (CSI) and their differences are an important basis for oil spill detection using visible/near-infrared (VNIR) remote sensing. Such features and differences can change with the observation geometry, affecting the identification accuracy. In this study, we carried out multi-angle reflection observation experiments of oil-contaminated sea ice (OCSI) and proposed a kernel-driven bidirectional reflectance distribution function (BRDF) model, Walthall–Ross thick-Litransit-Lisparse-r-RPV (WaRoLstRPV), which takes into account the strong forward-scattering characteristics of sea ice. We also analyzed the preferred observation geometry for oil spill monitoring in IISWs. In the validation using actual measured data, the proposed WaRoLstRPV performed well, with RMSEs of 0.0031 and 0.0026 for CSI and OCSI, respectively, outperforming the commonly used kernel-driven BRDF models, Ross thick-Li sparse (R-LiSpr), QU-Roujean (Qu-R), QU-Lisparse R-r-RPV (Qu-LiSpr-RrRPV), and Walthall (Wa). The observation geometry with a zenith angle around 50° and relative azimuth ranging from 250° to 290° is preferred for oil spill detection in IISWs.
... The ability to remotely detect and characterize oil and oil products in the Arctic marine environment has significant importance for local inhabitants, industry, and government. Presently, satellite remote sensing has been limited to the detection of oil in snow or at the snow-ice interface only [2] or in open water [3]. There is no direct method for satellite detection of oil within the ice volume or under the ice. ...
In this study, we performed a model-based analysis of scattering from oil-contaminated sea ice. Actual physical measurements of oil-contaminated sea ice were obtained from an experiment in 2017. We used a dielectric mixture model approach to create a multi-layered dielectric profile that represents the sea ice. For the first time, our multi-layered scattering model based on the small perturbation theory, was used to simulate scattering from oil-contaminated sea ice. Modeling results demonstrate that the method can be used for these conditions and show promise for further detailed model studies for detecting oil spills in a sea ice environment.
... A less technological approach is detecting oil by specially trained dogs. Sniffer dogs are already used to search out explosives and drugs, and their use for detecting oil buried under snow on sea ice has been field tested as part of the Oil in Ice-JIP (Brandvik and Buvik 2009;Dickens et al. 2010). This study found that the dogs were able to pinpoint the locations of very small oil spills that had been left for a week, determine the dimensions of larger oil spills consisting of clusters of small spills and indicate the direction to larger spills up to 5 kilometres away upwind. ...
Renewed political and commercial interest in the resources of the Arctic, the reduction in the extent and thickness of sea ice, and the recent failings that led to the Deepwater Horizon oil spill, have prompted industry and its regulatory agencies, governments, local communities and NGOs to look at all aspects of Arctic oil spill countermeasures with fresh eyes. This paper provides an overview of present oil spill response capabilities and technologies for ice-covered waters, as well as under potential future conditions driven by a changing climate. Though not an exhaustive review, we provide the key research results for oil spill response from knowledge accumulated over many decades, including significant review papers that have been prepared as well as results from recent laboratory tests, field programmes and modelling work. The three main areas covered by the review are as follows: oil weathering and modelling; oil detection and monitoring; and oil spill response techniques.
... It was concluded that a flexible combination of sensors operating from aircraft, helicopters, vessels, satellites and the ice surface is recommended for future Arctic oil spill emergency preparedness. However, detecting isolated oil patches trapped among closely packed ice floes is a major challenge with any current remote sensing system, particularly during periods of extended darkness (Dickins et al., 2010). The 2009 JIP oil in ice large scale field experiment has provided valuable information about oil spills in ice and state-of-the-art response techniques. ...
The blowout on the Ekofisk field in the North Sea in 1977 initiated R&D efforts in Norway focusing on improving oil spill contingency in general and more specifically on weathering processes and modeling drift and spreading of oil spills. Since 1978, approximately 40 experimental oil spills have been performed under controlled conditions in open and ice covered waters in Norway. The importance of these experimental oil spills for understanding oil spill behavior, development of oil spill and response models, and response technologies are discussed here. The large progress within oil spill R&D in Norway since the Ekofisk blowout has been possible through a combination of laboratory testing, basin studies, and experimental oil spills. However, it is the authors' recommendation that experimental oil spills still play an important role as a final validation for the extensive R&D presently going on in Norway, e.g. deep-water releases of oil and gas.
... For oil spill monitoring in the area of sea ice-infested waters, the VNIR remote sensing method has much more potential than SAR. Given the presence of sea ice, the conventional effective remote sensing methods, such as SAR, cannot identify oil slicks in waters with sea ice [5,[23][24][25][26]. Based on the reflectance and emissivity of the objects, however, VNIR remote sensing can eliminate oil slicks from the waters and sea ice [27]. ...
The reflectance of two commonly used oils, crude oil and diesel, is measured under various conditions: on a water surface, among pack ice, and on/beneath compact ice. The spectral characteristics of each oil are analyzed using the results from these measures. In conjunction with estimated noise thresholds of the sensor environment, the theoretical potential to identify oil is assessed for the hyperspectral Hyperion. The hyperspectral sensor is more sensitive to the crude oil than to diesel under all conditions. The visible and infrared bands, from 468 nm to 933 nm, are more suitable to identify the crude oil. In addition, when the background is pack ice, the infrared region from 1134 nm to 1326 nm is another potential useful zone. Through the visible-to-infrared bands, the sensitivity to the existence of diesel is inferior to that of crude oil. Relatively, the bands greater than 1134 nm have the potential to separate diesel from the water or sea ice. These characteristics and sensitivity of oil film in terms of ice and oil type can be effectively used to select suitable bands to distinguish oils from sea water and sea ice.
For more than 50 years, the oil and gas industry has jointly funded and conducted research with industry, government, academia, and stakeholders to advance and improve arctic oil spill response technologies and methodologies and understand the potential impacts on the marine environment. This sustained and frequently collaborative effort is not commonly known and recognised by those outside the field of oil spill response. This research has included hundreds of studies, laboratory and basin experiments and field trials, specifically in the United States, Canada and Scandinavia (Potter et al 2012). Recent examples include the SINTEF Oil in Ice JIP (2006–2009) (Sørstrøm et al 2010) and research conducted at Ohmsett - The National Oil Spill Response Research and Renewable Energy Test Facility.
To continue to build on this existing research, nine international oil and gas companies (BP, Chevron, ConocoPhillips, Eni, ExxonMobil, North Caspian Operating Company (NCOC), Shell, Statoil, and Total) are working collaboratively in the Arctic Oil Spill Response Technology - Joint Industry Programme (JIP). The purpose of the programme, the largest pan-industry programme dedicated to this area of research, is to further enhance industry knowledge and capabilities in the area of arctic oil spill response. The world's foremost experts on oil spill response, development, and operations from across industry, academia, and independent scientific institutions are being engaged to perform the scientific research.
The programme has completed phase one, which included technical assessments and state of knowledge reviews in the following six areas: dispersants, environmental effects, trajectory modelling, remote sensing, mechanical recovery, and in situ burning (ISB). Twelve research reports that identify and summarise the state-of- knowledge and regulatory status for using dispersants, in situ burn, mechanical recovery, and remote sensing in the Arctic are available on the JIP website (www.arcticresponsetechnology.org).
Phase two activities actively underway include modelling studies, laboratory and meso-scale basin testing and field experiments. Special emphasis is laid on gaining knowledge for the development of an Arctic Net Environmental Benefit Analysis (NEBA) tool to support operational decision-making for oil spill response strategy in the Arctic.
Space‐borne synthetic aperture radar has been proven to be a useful tool for ocean oil spill monitoring due to its large coverage, independence of the day–night cycle and all‐weather capability. In this paper, a method for oil spill detection based on a visual interpretation was applied to two consecutive Advanced Synthetic Aperture Radar (ASAR) images acquired during the Prestige oil spill off the Spanish coast. The obtained oil spill information was integrated into a Geographical Information System (GIS) database in order to study the spatial distribution and the evolution of the slicks between both days, in addition to carrying out a comparison with field observations. The results show the great capability of monitoring and forecasting marine oil spills caused by large oil tanker accidents by means of the use of radar imagery jointly with other information, such as wind data or in situ observations.
Space borne Synthetic Aperture Radars (SARs) have been used to observe and track the movement of marine oil spills for several years. SAR sensors possess many desirable characteristics for use in oil spill monitoring including; a wide field-of-view, foul weather independence, and day/night capabilities. On the other hand, spill response personnel have frequently been faced with some of the shortcomings of SAR sensors, sometimes unwittingly. Shortcomings of early space borne SAR sensors include: low spatial resolution, long revisit times, no positive means of oil detection, confusion with several false targets, and a limited wind speed "window" in which observation of oil is possible. The next generation of SAR sensors is currently coming on-stream and their enhanced capabilities can address some of the concerns voiced by spill response personnel. This paper will review the history of the use of SAR sensors as marine oil spill response tools, and illustrate some case studies where the use of SAR imagery has benefited.
With recent increased interest in oil and gas exploration and development in the Arctic comes increased potential for an accidental hydrocarbon release into the cryosphere, including within and at the base of snow. There is a critical need to develop effective and reliable methods for detecting such spills. Numerical modeling shows that ground-penetrating radar (GPR) is sensitive to the presence of oil in the snow pack over a broad range of snow densities and oil types. Oil spills from the surface drain through the snow by the mechanisms of unsaturated flow and form geometrically complex distributions that are controlled by snow stratigraphy. These complex distributions generate an irregular pattern of radar reflections that can be differentiated from natural snow stratigraphy, but in many cases, interpretation will not be straightforward. Oil located at the base of the snow tends to reduce the impedance contrast with the underlying ice or soil substrate resulting in anomalously low-amplitude radar reflections. Results of a controlled field experiment using a helicopter- borne, 1000-MHz GPR system showed that a 2-cm-thick oil film trapped between snow and sea ice was detected based on a 51% decrease in reflection strength. This is the first reported test of GPR for the problem of oil detection in and under snow. Results indicate that GPR has the potential to become a robust tool that can substantially improve oil spill characterization and remediation.
To obtain continuous profiles of the ice-water interface, a series of ground-penetrating radar (GPR) tests were performed. A GPR system was tested on lake ice as well as sea ice. Lake ice test was carried out in the National Petroleum Reserve-Alaska (NPR-A). The test consisted of scanning two separate lines 300 m long. The first line was placed on the airstrip where there was no snow cover, whereas the second, offset 10 m and parallel to the first line, was covered with windblown snow of varying thickness. The sea ice test was located offshore in Mikkelsen Bay near the Badami drill pad. To test the magnitude of the amplitude anisotropy of the radar signal, two perpendicular test lines were laid out. Velocities were obtained by linear regression and used to calculate permittivity. The reflection time was measured and the ice thickness was calculated using the average permittivity. Results were compared to the actual measured thickness and in general, they are slightly lower than the actual measured values. Nevertheless, evidence suggest that averaging several permittivity values is acceptable for use in ice profiling.
This paper describes the findings from an experimental spill of 3,400 liters of Statfjord crude under first-year sea ice in Svalbard, Norway in March 2006. The objectives were to:1. Test commercially available radar and acoustics systems for detecting oil spilled under ice.2. Document the weathering processes governing crude oil behaviour in ice.3. Confirm the effectiveness of in-situ burning as an oil removal strategy.
The results of this project will be used in planning new Arctic oil exploration and development programs. With the growing awareness of the Arctic basin as a potentially important province for new oil and gas discoveries, there is a critical need to: (1) develop new technologies to detect and map spills under ice; (2) increase the understanding of oil behaviour in ice and: (3) continue to demonstrate the capabilities of in-situ burning as an important and safe Arctic response tool.
Tank tests conducted in 2004 (Dickins et al., 2005) showed that radar systems could detect and map oil pools as thin as 2 to 3 cm under controlled conditions under model sea ice up to 40 cm thick. This field experiment created a much larger-scale spill under thicker 65 cm natural sea ice to further evaluate potential remote sensing systems as practical operational spill response tools.
The findings of the 2006 experiment: (1) demonstrated for the first time the ability of ground penetrating radar to detect and map oil under natural sea ice from the surface; (2) documented oil weathering with a relatively warm ice sheet under spring conditions; and (3) confirmed the effectiveness of in situ burning as a primary oil removal strategy under Arctic conditions.
Oil weathering results are discussed and compared with small-scale field experiments performed on Svalbard during the period 2003–2006. Low temperatures and lack of waves in ice act to reduce oil spreading, evaporation, emulsification and dispersion. As a result, the operational time window for several spill response strategies such as dispersants and in-situ burning may be significantly extended compared to oil spills in open water.
Results of impulse radar, ice crystal c axis, and subice current measurements on the fast ice near Narwhal Island, Alaska, are presented. The crystal structure of the ice was found to have a horizontal crystal c axis with a preferred azimuthal orientation. This orientation was found to align with the direction of the current at the ice-water interface. Impluse radar reflection measurements revealed that the preferred orientation of the sea ice crystal structure behaved as a microwave polarizer. It was observed that when the antenna E field was oriented parallel with the c axis of the crystal platelets, a strong reflection of the radar signal from the bottom of the ice was obtained. However, when the antenna E field was oriented perpendicular to the c axis, no bottom reflection was detected. The results of this study fully support earlier reports of sea ice inhomogeneity and anisotropy in reference to both structure and electromagnetic energy transmission.
Remote sensors for application to oil in ice and oil with ice are assessed. Radio-frequency methods to detect oil in ice depend on the difference in dielectric properties between oil and water. Freshwater ice is relatively transparent to frequencies below about 200 MHz. Despite extensive theoretical studies, there is a lack of experimental evidence to support the notion that radio-frequency methods have potential.Acoustic methods for the detection of oil in ice show promise. Regular metal inspection equipment is capable of detecting oil layers under ice. Oil propagates shear waves and detection methods based on this unique property are capable of identifying oil in ice. One unit has been built and tested in the field based on this principle.Oil with ice detection is a well developed technology. A common sensor is an infrared camera or an IR/UV (infrared/ultraviolet) system. The inherent weaknesses include the inability to discriminate oil on beaches, among weeds or debris. The laser fluorosensor is a most useful instrument because of its unique ability to identify oil on backgrounds that include water, soil, ice and snow. It is the only sensor that can positively discriminate oil on most backgrounds. Radar offers the only potential for large area searches and foul weather remote sensing, however, there is little potential to detect oil in the immediate vicinity of ice. A major weakness of radar is that it is limited to operation over seas with winds of about 2–8 m/s.Equipment operating in the visible region of the spectrum, such as cameras and scanners, is useful for documentation or providing a basis for the overlay of other data. It is not useful beyond this because oil shows no spectral characteristics in the visible region that can be used to discriminate oil.
Investigations of the in situ complex dielectric constant of sea ice were made using time-domain spectroscopy. It was found that (1) for sea ice with a preferred horizontal crystal c-axis alignment, the anisotropy or polarizing properties of the ice increased with depth, (2) brine inclusion conductivity increased with decreasing temperature down to about −8°C, at which point the conductivity decreased with decreasing temperature, (3) the DC conductivity of sea ice increased with increasing brine volume, (4) the real part of the complex dielectric constant is strongly dependent upon brine volume but less dependent upon the brine inclusion orientation, (5) the imaginary part of the complex dielectric constant was strongly dependent upon brine inclusion orientation but much less dependent upon brine volume. Because the electromagnetic (EM) properties of sea ice are dependent upon the physical state of the ice, which is continually changing, it appears that only trends in the relationships between the EM properties of natural sea ice and its brine volume and brine inclusion microstructure can be established.