Dynamic Modeling of Oil Spill Cleanup Operations

Transcription

1 16 Dynamic Modeling of Oil Spill Cleanup Operations Jared R. Eckroth 1, Mads M. Madsen 2, Espen Hoell 1 Proactima AS, Oslo, Norway 1, DHI, Hørsholm, Denmark 2 jared.eckroth@proactima.com Abstract For potential larger oil spills a contingency analysis must be implemented for establishing the necessary emergency preparedness measures. Operators must establish several contingency barriers covering the areas around oil production installations, the open seas, coastal zones and shorelines. The Norwegian Clean Seas Association for Operating Companies (NOFO) have guidelines for the emergency response analysis and theoretical uptake capacity for oil spill response systems, based on statistical weather and wave conditions. Actual uptake capacity is, however highly dependent on weather, wave height and oil conditions. This paper demonstrates a modeling tool for objective and real life analysis of alternative spill response strategies, using the MIKE 3 HD OS ( by DHI) modeling tool and actual weather situations as opposed to theoretical analyses, which are often in use. The tool models skimmers and booms with predefined capabilities and deployment strategies specified according to NOFO guidelines. It allows for dynamically positioning of the systems in response to the current weather situation either previously recorded (for planning and exercises) or forecasted for acute spill situations. The simulations provide answers to such questions as, How much oil is recovered at sea? What is the efficiency of the emergency measures? What is the reduction of oil amounts entering into vulnerable areas or ashore with or without the emergency measures? Additional benefits operators may achieve with the tool are as follows: 1. Improved positioning and efficiency of resources during real spill situations 2. Testing of mechanical recovery cleanup methods 3. More realistic training of emergency response personnel 4. Improved and verified emergency response plans for oil spill cleanup operations 1 Introduction As part of the project Update of Environmental Risk Analysis (ERA) and Oil Spill Emergency Preparedness Analysis (OSEPA) for the Alvheim field previously operated by Marathon Oil Norway (now Det Norske ASA), a study was initiated with the aim to include calculations of emergency preparedness efficiency integrated with oil drift simulations. The main objective of the study was to investigate the efficiency/capabilities of mechanical recovery oil spill cleanup equipment based on recorded weather data. At present there are several established models e.g. PISCES, ROC, OSCAR, SIMAP which also perform efficiency modeling for mechanical responses. However, to the best of the author s knowledge not using a dynamic modeling approach as described in this paper. What is meant by the term dynamic modeling is that wind, waves and ocean currents at every time step are changing which will result in changing the drift path of the oil slick, as would be happening in real life situations. The user has the option of moving the equipment at any time, in response to

2 17 the changing conditions, so as to efficiently recover as much oil as possible. However the weather forces acting on the slick can create challenges in recovery as the equipment may not always be able to keep pace with the changing dynamics of the slick. Emergency vessels may try to position themselves in front of the thickest patches of oil but by the time they start operating the drift direction may change, thus requiring the equipment to be repositioned. As for all models using a Lagrangian particle approach some characteristics of the oil slick would not fit the true nature of a real oil slick e.g. oil slicks have will have most of the oil volume concentrated in a small area while the modeled slick will have the volume equally distributed. Equations addressing the fact that oil particles aggregate in some areas will be considered in future revisions of the tool. The model resolves down time of the equipment (e.g. caused by cleaning / technical fixes, emptying / transfer collected oil emulsion, or limitations relating to personnel, expertise etc) by reducing the nominal pumping capacity of the systems. The tool also accounts for reduced recovery due to wind speed, wave height and night visibility. Through dynamic modeling the user gains knowledge on how an actual spill evolves and how cleanup strategies and equipment positioning need to be adapted in order to enable a successful oil recovery operation. In the present model context hind casts of metocean conditions have been applied. In case of actual spills the same concept can apply if the model is operated in a forecast mode. Equipment performance specifications and prerequisites, as defined by manufacturers (Nordvik, 1999; NOFI, 2015), Norsk Oljevernforening For Operatørselskap (NOFO) (NOFO, 2007) and Norsk Olje og Gass (Norsk Olje og Gass, 2013), has been implemented in the applied modeling tool. This paper provides results from oil spill cleanup simulations performed. 2 Method 2.1 Model Description and Location A prerequisite for any kind of oil spill modeling is reliable oceanographic hind cast (or forecast) data with respect to currents, wave conditions and wind speeds. The present investigation utilizes an existing validated hydrographic model (DHI, 2014a) based on the MIKE, by DHI, Flexible Mesh (FM) 3D hydrodynamic model system with a coupled oil spill (OS) module. The model provides the relevant metocean data on an hourly basis and covers meteorological hindcast for a number of years. Validation has been carried out based on combined local current measurements and oceanographic data on water level, currents, salinity and water temperature. The model covers all Norwegian Seas and beyond with resolution in space varying from approx. 8 km grid offshore and down to m along the coast and fjords. For this study a detailed model grid was applied around the Alvheim Field is depicted in Figure 1. In this area the resolution are 250 m. The model is forced with meteorological data (atmospheric pressure, wind, ice, 2 m air temperature, humidity, precipitation and cloudiness) from National Centers for Environmental Prediction s (NCEP) Climate Forecast System Reanalysis (CFSR) and tidal elevation from DTU10 global ocean tide model (which is an update of the AG95 ocean tide). Besides tides, the open boundary forcing (salinity, sea water temperature, oceanographic currents and sea surface heights) are provided from MyOcean and Mercator PSY3V3R1 global reanalysis model. Wave data are likewise extracted from DHI s existing Global Wave Model hindcast covering the period (DHI, 2014b).

3 18 Figure 1. Left: Alvheim in the Northern part of the North Sea, Right: modeled area in MIKE (snap shot of the currents in the area). The spill modeling (Figure 2) is based on the MIKE 21/3 OS module (a particle tracking oil spill module), which simulates the movement of discrete particles (Lagrangian approach) in a flow field. Each (oil) particle has an associated mass, which can change as a result of weathering processes. A coupled MIKE 21/3 Eulerian Advection-Dispersion module allows for proper simulation of the spreading of dissolved hydrocarbons. Figure 2. Oil weathering processes in MIKE 21/3 OS.

4 19 MIKE 21/3 OS includes a number of features such as: Relevant weathering processes (Spreading (viscous, gravity based), evaporation, emulsification, vertical dispersion (by waves), dissolution, biodegradation, photo-oxidation Movement of the oil on the surface and in the water column Sub-sea blowout (oil and gas mix) Effects of adding dispersants Clean-up using booms and skimmers Stranding with the possibility of re-entering the water Ice edge interaction with the possibility of re-entering the water 2.2 Oil Characteristics For this analysis Alvheim Blend was used. This oil type consists mainly of the crudes Kneler, Vilje, Boa, Volund and Kameleon (SINTEF 2009). The weathering properties for Alvheim Blend are summarized in Table 1. Table 1. Characteristics of Crude Oil (Alvheim Blend) Oil Type Parameter Value Density (g/ml) 0,84 Emulsion Water content will be relatively low (~50%) Wax content (wt. Alvheim 5,3 %) blend Asphaltenes (wt. 0,06 %) Pour Point ( C) -3 Viscosity (mpas) 18 FlashPoint( C) Simulation Setup Simulations were performed for a typical summer and winter situation. The same oil properties and oil release rate were used for both summer and winter scenarios, and both with and without emergency response systems. The spills were released at the Alvheim FPSO position in the North Sea (Lat, Long: N, E), on the sea bottom (125 m depth) for a 24 hour period. Distance to the coastal zone is 175 km. Table 2 displays simulations preformed and their respected durations. NOFO (NOFO 2007) and Norsk Olje og Gass (Norsk Olje og Gass, 2013) guidelines require 4 barriers being established when combating oil spills. Barrier 1 and 2 are located close to the origin of the spill, barrier 3 is located in the coastal zone and barrier 4 is shoreline cleaning. For the purpose of this project only barriers 1 and 2 were simulated. After the entire oil slick had drifted through the 2 barriers the cleanup operation stopped, while the oil was allowed to drift to allow for further weathering and possible stranding. The reason was to test the initial effectiveness of the equipment with regards to changing weather using a short duration spill scenario. In real life situations, the NOFO vessels in Barrier 1 and 2 would continue to combat

5 20 oil throughout the drift path and additionally barriers 3 and 4 would be in place for coastal oil recovery. Table 2. Summary of Simulations. Season Winter Summer Start time 13/01/12 at 16:00 07/13/20 12 at 04:00 Amoun t of oil release d (kg) Use of mechanica l recovery Spill duratio n (days) Duration of oil recovery operatio n (days) Trackin g of oil slick (days) No Yes No Yes Total length of simulatio n (days) 2.4 Equipment Efficiency A NOFO system for a mechanical recovery operation includes one NOFO oil recovery vessel, one tug vessel, one oil boom, and one Trans-rec skimmer, and has a catchment width of about 300 meters as shown in Figure 3. With more NOFO systems joining the cleanup operation, the systems were placed next to each other. Figure 2.NOFO systems description and layout (NOFO, 2015) The trans-rec skimmer is estimated to have a daily pump rate of about 8000 Sm 3 (Nordvik 1999) however when collecting oil to recover, repositioning of the system, emptying of the oil onto tankers and general maintenance of the vessel are all taken into consideration the nominal system capacity is defined to 2400 Sm 3 (Norsk Olje og Gass, 2013), used as the nominal capacity in the simulations. In this study NOFO systems were represented as line with a length proportional to the sum of the distances of the catchment openings for the number of systems present, e.g. 3 systems have a catchment distance of 900 meters in the simulations.

6 21 The vessels were positioned manually downstream of the oil drift path, were the bulk of oil was present, assuring ocean currents to push the oil into the booms. As the ocean currents and drift paths changed, the systems were repositioned to where significant amounts of oil were present. Distances traveled were always in proportion to the vessel cruising speed. The parameters listed in Table 3 have been included in the modeling. Actual daylight, significant wave heights, surface currents and wind speeds from the Alvheim field location are forcings to the oil spill simulations whereas properties like e.g. viscosity and slick thickness is computed by the MIKE OS model at each time step. The tables parameters are based on references listed in Table 3. Table 2. Parameters Used to Calculate Recovered Oil Condition Parameter Wind (m/s) (NOFI 2015) If wind speed 14 m/s than probability for boom leakage = 100 % Wave (Hs) (Norsk Olje og If significant wave height (Hs) 2 m than = no boom leakage Gass 2013) Or If Hs 2 m and 4 m than probability for boom leakage = (0.5*Hs)-1 Or If Hs 4m than probability for boom leakage will be 100% Surface currents (m/s) (Oil If surface currents 0.36 m/s then probability for boom leakage Spill Sollutions 2014) = 20 % Daylight (Norsk Olje og If sun is lower than 6 under the horizon 20% reduction in system Gass 2013) Viscosity (cp) (Nordvik 1992) Oil thickness (mm) (Lewis 2007), Norsk olje og gass 2013) Vertical position of oil particle (m) (NOFI 2015) efficiency If viscosity is 1000 cp then probability for boom leakage = 0 Or If viscosity is 1000 cp than probability for boom leakage = ( * viscosity +1) If thickness is 0.1mm than no boom leakage Or If thickness 0.1 mm than probability for boom leakage = (-10(thickness)+1) If oil is 1m below ocean surface than oil will pass under the boom Equipment requirements were based on Alvheims 2014 Oil Spill Emergency Preparedness Analysis (OSEPA) (Proactima, 2014) and calculated seasonal uptake efficiencies based on Norsk oil and gas guidelines (Norsk Olje og Gass, 2013). For winter operation it was recommend 9 NOFO systems. For summer operation, using only mechanical recovery, it was recommended 6 NOFO systems. Arrival times of all NOFO vessels were based on distance to spill site, sailing speed, time to load equipment and personal and finally time taken to set out the skimmers and booms once at the spill site.

7 22 3 Results 3.1 Winter Weather Figure 4, Figure 5 and Figure 6 shows significant waves heights, wind speeds and wind directions for the first 48 hours of the spill. The figures show the first and last arrival times of the NOFO systems and the actual weather at the time of arrival. High wave heights and strong winds assist in naturally dispersing of the oil, while sudden changes in wind direction spread the oil over greater areas. This make mechanical recovery more difficult as the vessels will have a greater area of oil to recover in addition to high wave heights. Figure 4. Significant wave height (Hs) for the first 48 hours of the simulation. Arrows show first and last arrival time of NOFO vessels.

8 23 Figure 5. Wind speed (m/s). Figure 6. Direction (degrees) for the first 48 hours of the simulation. During the simulation the wind is shifting from an almost northerly wind toward a southwesterly wind direction. Rapid changes in wind direction are observed. 3.2 Winter - Mechanical Recovery After the arrival of the first NOFO vessel the wave height is 3.2 meters (Figure 4) implying greatly reduced recovery efficiency. As the simulation continues there is a sudden drop in the wind speed (Figure 5) and steady decreases in wave height. This allows for a more efficient recovery of oil as more NOFO systems join the operation. However for most of the cleanup the wave height is still above 2 meters which associated to relatively strong wind speeds. Further the recovery efficiency decrease due to this being a wintertime operation with limiting amounts of day light. Changes in wind direction affect the drift course and reduce the uptake efficiency as the NOFO vessels have to reposition to stay in the drift path. Finally the model also takes into account periods when the oil is being pushed down in the water column by the waves. In the simulations a threshold of 5 m/s of wind were used as a cut off in determining if the oil could be pushed under the surface by waves and the distance pushed was always proportional to the wave height (Delvigne and Sweeney, 1989). The oil slick reached the viscosity of 1000cP and a film thickness of 0,1mm before the NOFO vessels arrived and thus did not reduce the uptake efficiencies. Figure 6 shows the mass budget for the oil mass and emulsion removed and remaining when emergency measures are applied, and compares the amounts that would otherwise remain without mechanical recovery. The emulsion includes, in principle all fractions: volatile, semi volatile, heavy fraction, wax and asphaltenes in addition to the water uptake. However the volatile fractions will evaporate quickly, usually within 24 hours.

9 24 Figure 7. (Top) shows the mass (kg) budget for Alvheim Blend with no emergency measures are applied. Blue line represents the emulsion while the black line represents only the oil mass. (Bottom) shows the mass (kg) budget for Alvheim Blend when 9 NOFO vessels using mechanical recovery are simulated. Blue line represents the emulsion while the black line represents only the oil mass. In total about 50 % of the oil is degraded due to various weathering processes, but due to the uptake of water the mass of the oil emulsion is only 5 % less than the total amount released, implying that emulsification almost doubles the mass. The overall efficiency of the 9 NOFO systems is that 50.6 % of the emulsion is removed. Each system is able to remove on average 5.6 % of the total emulsion. If the emergency operation had been applied to the remaining drift path, it is assumed that the recovery could have been increased further. The remaining oil was further tracked after the initial 48 hours in both

10 25 simulations to allow for potential stranding. However in the winter simulation stranding did not occur. Table 4 lists the remaining amounts of the heavy mass fraction of the oil for both with and without applying emergency measures after 32 days at sea. Only 9.5 % of the heavy mass fraction of the oil is weathered away naturally, while the 9 NOFO systems remove 57.0 % of the heavy fraction of oil i.e. an increase of 47.5 % efficiency. Table 4. Heavy mass fraction of oil remaining after 48 hours and 31 days for both with and without the use of emergency measures. Scenario Heavy oil mass left (tons) Total amount 1597 (released) No booms 48 hours 1586 (remaining) No booms 31 days 1446 (remaining) 9 Booms (remaining) hours 9 Booms 31 days 686 (remaining) Figure 8 shows the remaining oil after 48 hours with and without application of mechanical recovery.

11 26 Figure 8. (Top) remaining oil particles after 48 hours near that Alvheim spill site. (Bottom). Remaining oil particles after 48 hours when 9 NOFO vessels are used to mechanically remove the oil near the Alvheim spill site. Blue particles representing oil that has been pushed into the water column by the wind and wave action, while the red particles represent oil which is on the surface of the ocean and would be available for mechanical recovery. Figure 9 represents the last time step of the 31 day simulation during the winter period. The remaining oil mass (kg) is primarly composed of the heavy fraction of the oil mass and the absorbed water.

12 27 Figure 9. The top figure shows the oil mass (kg) when oil is present when no emergency measures are applied while bottom figure shows oil mass (kg) when 9 NOFO systems were applied to mechanically remove the emulsion. 3.3 Summer Weather Figure 10, Figure 11 and Figure 12 shows significant waves heights, wind speeds and wind directions. Further the figures show the first and last arrival times of the NOFO systems. Low wave heights but strong winds and higher temperatures will assist in naturally disperse the oil faster, while sudden changes in wind direction will assist in spreading the oil over greater areas.

13 28 Figure 10. Significant wave height (Hs) for the first 48 hours of the simulation. Arrows show first and last arrival time of NOFO vessels. Figure 11. Wind speed (m/s) and Right: wind direction (degrees) for the first 48 hours of the simulation.

14 29 Figure 12. Wind direction (degrees) for the first 48 hours of the simulation. 3.4 Summer - Mechanical Recovery When the first NOFO vessel arrives the wave height is above 1 m (Figure 10) implying that oil will be recovered with relatively high efficiencies. There are however, still long periods where the wind (Figure 11) is above 5 m/s which will assist in pushing the oil into the water column in proportion to the wave height, thus limiting the times when mechanical recovery is possible. In addition sudden changes in the ocean currents and wind direction result in changes in the drift course of the oil slick. This complicates the positioning of the NOFO vessels and requires that they must frequently reposition themselves to stay in front of the drifting oil. Finally, since the number of NOFO vessels are reduced by 1/3 (to 6, calculated for summer conditions), the catchment area has been reduced accordingly, The oil slick reached a viscosity of 1000cP and film thickness of 0,1mm before the NOFO vessels arrived and thus did not reduce the uptake efficiencies (SINTEF 2009). Figure 13 shows the mass budget for the oil mass and oil emulsion removed and remaining in the simulations when emergency measures are applied and compares the amounts that would otherwise remain had mechanical recovery operations not been implemented after 48 hours.

15 30 Figure 13. (Top) shows the mass (kg) budget for Alvheim Blend with no emergency measures are applied. Blue line represents the emulsion while the black line represents only the oil mass. (Bottom) shows the mass (kg) budget for Alvheim Blend when 6 NOFO vessels using mechanical recovery are simulated. Blue line represents the emulsion while the black line represents only the oil mass. In total about 50 % of the oil is degraded due to various weathering processes, but due to the uptake of water the mass of the oil emulsion is only 5 % less than the total amount released meaning that emulsification almost doubles the mass. This was the same as the winter simulation. This means that evaporation and natural degradation of the oil happens at about the same rate as the uptake of water. 6 NOFO systems were able to remove 43.0 % of the emulsion. Each system is able to remove on average 7.1 % of the total emulsion. The systems were able to remove an additional 21 % of the actual oil mass as compared when no emergency measures are applied.

16 31 For this simulation the remaining oil after 48 hours was further tracked in 30 days to allow for stranding. However this did not occur in the simulation as was also the case during the winter simulation. Table 5 lists the remaining amounts of the heavy mass fraction of the oil for both with and without applying emergency measures. Only 30.8 % of the heavy mass fraction of the oil is weathered away after 32 days while when adding in the 6 NOFO systems in total 59.8 % of the heavy fraction of oil which is removed, which is in increase of 29.0 % efficiency. Table 5. Heavy mass of oil remaining after 48 hours and 31 days for both with and without the use of emergency measures. Scenario Heavy oil mass left (tons) Total amount 1597 (released) No booms 48 hours 1587 (remaining) No booms 31 days 1104 (remaining) 6 - Booms- 48 hours 909 (remaining) 6 - Booms 31 days 641 (remaining) Figure 14 shows the remaining oil spill at 48 hours after commencement for both with and out the application of emergency measures.

17 32 Figure 14. (Top) remaining oil particles after 48 hours near that Alvheim spill site. (Bottom). Remaining oil particles after 48 hours when 9 NOFO vessels are used to mechanically remove the oil near the Alvheim spill site. For both figures are the blue particles representing oil that has been pushed into the water column by the wind and wave action, while the red particles represent oil which is on the surface of the ocean and would be available for mechanical recovery at the last time step. Figure 15 represents the last time step of the 31 day simulation during the winter period. The different colors represents the remaining oil mass (kilograms) which is primarly compsed of the heavy fraction of the oil mass and the absorbed water.

18 33 Figure 15. The left figure shows the oil mass (kg) when oil is present when no emergency measures are applied while right figure shows oil mass (kg) when 6 NOFO systems were applied to mechanically remove the emulsion. 4 Conclusion In our simulations there were five main factors that were effecting cleanup operations. 1. Oil rapidly spread over large areas and the catchment areas of the NOFO vessels simply were not large enough to catch all the oil. This resulted in large quantities of oil passing the barriers. 2. Frequent changes in the ocean currents which resulted in need for rapid repositioning of the vessels in order for them to stay in front of the drift path of the oil. 3. Waves pushing the oil under the booms and not allow for mechanical recovery until the oil resurfaced. 4. Significant wave height. Although this was less problematic during the summer oil spill recovery operations it did reduce the booms efficiency during the winter recovery operations. It should be noted however that higher significant wave heights will help in natural dispersion of the oil. 5. Amount of daylight. Longer proportion of daylight in Norwegian summers increase efficiency of emergency preparedness. Natural degradation of the oil resulted in 50 % reduction of the total oil mass during both summer and winter periods after the NOFO systems are allowed to operate in 24 hours after the spill has ended. However due to water uptake the volume of the emulsion was almost the same size as the original oil mass after 48 hours without the use of mechanical recovery.

19 34 During the winter when 9 NOFO systems were used for a mechanical recovery operation the total oil mass was reduced by an additional 25 % after 48 hours while the emulsion was reduced by 50 % as compared to natural weathering of the oil. During the summer 6 NOFO systems reduced the total oil mass by 21 % while the emulsion was reduced by 43 % after 48 hours when compared to amounts remaining after natural weathering took place. Even though a higher percentage of the emulsion was removed during the winter, individual vessels were more effective during the summer. The efficiency of the operation could be improved by letting the systems operate of a longer proportion of the drift time. After 32 days of tracking the oil had not stranded. Given more time it could still be possible for stranding to occur. However it is still be possible to make some reasonable predictions in regards to the % of reduction in the amounts of oil stranding. In general it could be assumed that the total % of emulsion removed by the NOFO systems would reduce stranding by at least this percentage. The longer the emulsion remains at sea the further it will weather and degrade into the water column. This will also reduce the amounts of oil hitting the coast, but by how much is very weather dependent. From the simulation results, stranding could be reduced by at least 50 % during winter and 43 % during summer, and even more if the NOFO vessels were allowed to operate longer. Additionally oil would further be reduced by a certain percentage based on how much more time the oil would be allowed to weather and degrade during the drift time to the coast. When tracking the oil for an additional 30 days the remaining emulsion was further reduced by 13.5 % during the winter and 29.5 % during the summer. From this example the weather situation plays an important role with regards to the amounts of oil that will be further degraded and thus reducing the amounts stranding on the coast. The application of chemical dispersants was not implemented in this study but is currently being developed and will be available for future oil recovery simulation studies. Other oil recovery simulation tools allow for the thickest parts of the oil slick to be automatically removed at a certain rate based on equipment capabilities and using limited weather situations. By using a dynamic modeling approach, with the use of previously recorded (or forecasted) weather e.g. wind, waves, currents, the mechanical recovery operation requires a constant response to the changing oil drift path, fluctuations in weather and devise a cleanup strategy throughout the simulation. This approach brings the operator closer to how a real oil spill cleanup situation would play out, thus improving knowledge of how to best respond to future spills. 5 References Delvigne, G.A.L. and C.E. Sweeney, "Natural dispersion of oil", Oil and Chemical Pollution 4: , 1989 DHI (2014a). Northern North Sea, Norwegian Sea and Barents Sea 3D Hydrodynamic Model. Set-up, Validation and Hindcast of 2011 and Horshølm, Denmark, DHI. DHI (2014b). DHI Global Wave Model, Set-up, Calibration, Validation and Hindcast Hørsholm, Denmark, DHI.

20 35 Lewis, A. (2007). Current Ststus of the BAOAC (Bonn Agreement Oil Appearance Code): 19. NOFI (2015). Retrieved Feb 26, 2015, from NOFO (2007). Veileder for miljørettet beredskapsanalyser NOFO (2015). Retrieved January 15, 2014, from %20av%20NOFO.pdf. Nordvik, A.B., "Summary of development and field testing of the transrec oil recovery system.", Spill Science & Technology Bulletin 5: , Nordvik, A.B., P. Daling, and F.R. Engelhardt, Problems in the interpretation of spill response technology studies, Proceedings of the 15th AMOP Tecnical Seminar, Environment Canada, Ottawa, ON, Canada., Vol. 2, Norsk Olje og Gass (2013). Veiledning for miljørettede beredskapsanalyser. Oslo, Norway, Norsk Olje og Gass: Oil Spill Sollutions (2014). Retrieved Feb, 26, 2015, from Proactima (2014). Alvheim miljørisiko og beredskapsanalyse - Updated analysis for Alvheim, Volund, Bøyla and Vilje. SINTEF (2009). Weathering properties of the Alvheim crude oils Kneler, Boa, Kameleon, and the Alvheim blend. Trondheim, Norway: