Numerical Simulation on Oil Spilling of Submarine Pipeline and Its Evolution on Sea Surface

Due to the interaction and corrosion of the seawater,submarine pipelines are easy to be broken to spill oil.The special environment of subsea restricts the technical development of pipeline maintenance.Therefore,the study on the oil spilling model of submarine pipeline is very important for predicting the movement and diffusion of spilled oil,so that oil spilling traces and relating strategies can be determined.This paper aims to establish an oil spilling model of a submarine pipeline,study the movement characteristics of spilled oil in seawater by numerical simulation,and determine the traces,diffusion range,time to sea surface,etc.Then,the maximum horizontal migration distance(MHMD)with corresponding time are analyzed under different oil densities,spilling speeds and seawater velocities.Results show that the MHMD decreases first and then increases while the time to achieve the MHMD increases along with increasing oil density.The MHMD increases while the time to achieve the MHMD decreases,along with increasing spilling speed.Both the MHMD and corresponding time increase along with increasing seawater velocity.Based on numerical results,a correlation of spilling distance and spilling time is proposed to give fast and accurate predictions.After the oil reaches sea surface,oil expansion and transport are simulated.Euler-Lagrange method is used in the simulation.Dynamic and non-dynamic factors are considered.Results show that wind velocity and water velocity are dominant in dynamic factors.When they are large,spilled oil moves very fast with variable directions in complex flow field.Nondynamic factors such as evaporation,emulsion and solution mainly reduce the volume of oil film.They almost do not affect the direction and displacement of spilled oil.Quick response should be made for large wind and water velocities when the placement of oil boom is given.With the correlation and simulation,emergency responses can be guided effectively to reduce the impact of submarine oil pollution.The computational results benefit pollution control and environmental protection in marine petroleum engineering.

A CFD Model to Evaluate Near-Surface Oil Spill from a Broken Loading Pipe in Shallow Coastal Waters

Oil spills continue to generate various issues and concerns regarding their effect and behavior in the marine environment,owing to the related potential for detrimental environmental,economic and social implications.It is essential to have a solid understanding of the ways in which oil interacts with the water and the coastal ecosystems that are located nearby.This study proposes a simplified model for predicting the plume-like transport behavior of heavy Bunker C fuel oil discharging downward from an acutely-angled broken pipeline located on the water surface.The results show that the spill overall profile is articulated in three major flow areas.The first,is the source field,i.e.,a region near the origin of the initial jet,followed by the intermediate or transport field,namely,the region where the jet oil flow transitions into an underwater oil plume flow and starts to move horizontally,and finally,the far-field,where the oil re-surface and spreads onto the shore at a significant distance from the spill site.The behavior of the oil in the intermediate field is investigated using a simplified injection-type oil spill model capable of mimicking the undersea trapping and lateral migration of an oil plume originating from a negatively buoyant jet spill.A rectangular domain with proper boundary conditions is used to implement the model.The Projection approach is used to discretize a modified version of the Navier-Stokes equations in two dimensions.A benchmark fluid flow issue is used to verify the model and the results indicate a reasonable relationship between specific gravity and depth as well as agreement with the aerial data and a vertical temperature profile plot.

Research Status of Technical Specifications for Bioremediation of Shorelines Polluted by Spilling Oil

Bioremediation of shorelines polluted by spilling oil has no secondary pollution and saves manpower and material resources, so it has a wide market. Standardizing the operation methods and materials used of the technology can improve its efficiency. Therefore, the research process of technical specifications for bioremediation of shorelines polluted by spilling oil at home and abroad was expounded in this study.

Oil Spill Risk Assessment of Offshore Pipeline in the Bohai Sea Under the Perspective of Ecological Protection

In recent decades,the exploration and development of marine oil and gas resources have increased significantly to meet the increasing energy demand of mankind.The Bohai Sea is a semi-closed continental sea that has a weak water exchange capacity and high ecological fragility.However,at present,more than 200 oil platforms have been built in the Bohai Sea,with more than 270 offshore oil pipelines having a length exceeding 1600 km.The oil spill pollution of offshore platforms has a great impact on the marine environment and ecosystems.Therefore,a comprehensive assessment of its risks is of great practical significance.This paper systematically constructs a comprehensive oil spill risk assessment model that combines the oil spill risk probability model and the ocean hydrodynamic model.This paper uses the Bohai Sea offshore pipeline as an example to assess its oil spill risk.The high-risk-value areas of the Bohai Sea offshore pipeline are mainly distributed at the bottom of Liaodong Bay,the bottom of Bohai Bay,near the Caofeidian area,and the northern part of the Yellow River Estuary.

Transport and behavior of marine oil spill containing polycyclic aromatic hydrocarbons in mesocosm experiments

Polycyclic aromatic hydrocarbons(PAHs)are one of the most important groups in oil,and re sponsible for major toxic and/or carcinogenic impact on humans and wildlife.It is important to understand the behavior of PAHs in marine environment after an oil-spill incident.However,interaction between petroleum PAHs and microbial communities in a marine environment remains unclear.Therefore,a series of mesocosm experiments were conducted.in which water-accommodated fraction(WAF)of oil was generated to simulate an oil-spill scenario and to analyze the transport and behavior of marine oil spill containing PAHs with and without dispersants.Results indicate that the application of dispersant could increase the concentration of total PAHs in water column due mainly to significant increase in the concentration of highmolecular weight(HMW)PAHs at a lower removal rate.At the end of the 7-day experiment,significant amount of HMW PAHs were accumulated in sediment.In general,the application of dispersant did not increase the sediment uptake of PAHs but increased the PAHs concentration in water column.

Parameterization Method of Wind Drift Factor Based on Deep Learning in the Oil Spill Model

Oil spill prediction is critical for reducing the detrimental impact of oil spills on marine ecosystems,and the wind strong-ly influences the performance of oil spill models.However,the wind drift factor is assumed to be constant or parameterized by linear regression and other methods in existing studies,which may limit the accuracy of the oil spill simulation.A parameterization method for wind drift factor(PMOWDF)based on deep learning,which can effectively extract the time-varying characteristics on a regional scale,is proposed in this paper.The method was adopted to forecast the oil spill in the East China Sea.The discrepancies between predicted positions and actual measurement locations of the drifters are obtained using seasonal statistical analysis.Results reveal that PMOWDF can improve the accuracy of oil spill simulation compared with the traditional method.Furthermore,the parameteriza-tion method is validated with satellite observations of the Sanchi oil spill in 2018.

The Mitigation Strategies for Managing the Potential Environmental Risks Posed by Oil and Gas Development on Mangrove Ecosystems in the Coastal Communities

Guyana is an oil-producing country vulnerable to potential oil spills and the environmental risks posed by oil and gas exploration and production activities. Despite the technologically advanced equipment employed by ExxonMobil Guyana and affiliates, an oil spill could occur due to accidents, equipment failures, or sabotages. The selected coastal communities as the study areas in Region 1 and Region 2 could be adversely affected, particularly the mangrove ecosystems. Potential oil spill pollution will adversely impact mangrove ecosystems in Region 1 and Region 2. Mangroves offer significant benefits to coastal communities, such as coastal defence and carbon sequestration, which puts Guyana on the world map. The research aimed to investigate the mitigation strategies to manage the potential environmental risks on mangrove ecosystems in the coastal communities of Region 1 and Region 2. It followed a qualitative approach and conducted semi-structured interviews with the Toshaos of the selected coastal communities. The data analysis strategy was thematic analysis using the Nvivo software. The major themes included legal and policy frameworks, oil spill response strategies, community-based involvement, and monitoring and enforcement of regulations. The significant results included reviewing and updating the regulatory framework for mangrove management and conservation;oil spills mitigation measures such as containment and shoreline protection and cleanup, cost recovery and compensation, and limited monitoring and law enforcement of mangrove management and conservation regulations by inter-agencies. The regulatory and institutional framework is outdated and needs to be amended. The agencies overseeing mangrove management and conservation have overlapping responsibilities and require more coordination. There should be greater collaboration among agencies for mangrove management and conservation and improved monitoring and enforcement programmes through institutional support.

The Environmental Risks Posed by the Oil and Gas Development and Its Potential Impacts on Mangrove Ecosystems and the Coastal Community’s Well-Being

Guyana is an oil-producing country with oil and gas exploration and production operations approximately 190 km offshore. The coastal communities selected as the study areas in Region 1 and Region 2 are adjacent to the coast and 5 to 10 km inshore. In the event of oil spills, Shell Beach Protected Areas and the other selected communities will be negatively impacted, particularly the mangrove ecosystems and the community’s well-being. The research aims to investigate the potential environmental risks posed by oil and gas exploration and production activities. It followed a qualitative approach and employed semi-structured interviews with the Toshaos of the coastal communities. The data analysis strategy was thematic analysis using the Nvivo software. The major themes included community assets, the importance of mangrove ecosystems, and the impacts of mangrove ecosystem damage through oil spills. Oil spill pollution will negatively impact mangrove ecosystems and the coastal community well-being in Region 1 and Region 2. The major results include damage to cultural artefacts, saltwater intrusion of major creeks, reduced fish catch levels, and agriculture products, which are the main economic activities in the selected communities. Consuming contaminated agriculture and marine products will lead to adverse health problems. Mangrove ecosystems provide considerable benefits to coastal community residents, including shields against river bank erosion, natural habitats for wildlife and source of income, shared traditions, social values, recreational facilities, and tourist attractions. These benefits contribute to the overall coastal community’s well-being. The mangrove forests must be protected and conserved to avoid environmental damage.

Application of Vegetation Indices for Detection and Monitoring Oil Spills in Ahoada West Local Government Area of Rivers State,Nigeria

The study evaluated the environmental effects of an oil spill in Joinkrama 4 and Akimima Ahoada West LGA,Rivers State,Nigeria,using various vegetation indices.Location data for the spill were obtained from the Nigeria Oil Spill Detection and Response Agency,and Landsat imagery was acquired from the United States Geological Survey.Three soil samples were collected from the affected area,and their analysis included measuring total petroleum hydrocarbons(TPH),total hydrocarbons(THC),and polycyclic aromatic hydrocarbons(PAH).The obtained data were processed with ArcGIS software,utilizing different vegetation indices such as the Normalized Difference Vegetation Index(NDVI),Atmospheric Resistant Vegetation Index(ARVI),Soil Adjusted Vegetation Index(SAVI),Green Short Wave Infrared(GSWIR),and Green Near Infrared(GNIR).Statistical analysis was performed using SPSS and Microsoft Excel.The results consistently indicated a negative impact on the environment resulting from the oil spill.A comparison of spectral reflectance values between the oil spill site and the non-oil spill site showed lower values at the oil spill site across all vegetation indices(NDVI 0.0665-0.2622,ARVI-0.0495-0.1268,SAVI 0.0333-0.1311,GSWIR-0.183-0.0517,GNIR-0.0104--0.1980),indicating damage to vegetation.Additionally,the study examined the correlation between vegetation indices and environmental parameters associated with the oil spill,revealing significant relationships with TPH,THC,and PAH.A t-test with a significance level of p<0.05 indicated significantly higher vegetation index values at the non-oil spill site compared to the oil spill site,suggesting a potential disparity in vegetation health between the two areas.Hence,this study emphasizes the harmful effect of oil spills on vegetation and highlights the importance of utilizing vegetation indices and spectral reflectance analysis to detect and monitor the impact of oil spills on vegetation.

Degradation of crude oil by indigenous microorganisms supplemented with nutrients

Different kinds of mineral nutrients(NO_3-N, NH_4-N and PO_4-P) were applied in the simulated oil-polluted seawater for enhancing oil biodegradation in the N/P ratio 10∶1 and 20:1 Although indigenous microorganisms have the ability to degrade oil, adding nutrients accelerated biodegradation rates significantly. For the group amended with NO_3-N and PO_4-P in the ratio 10∶1, the reaction rate coefficient was 4 times higher than the natural biodegradation. Chemical and microbiological analysis showed that the optimal N/P ratio in the system is 10∶1, and microorganisms tend to utilize nitrate rather than ammonium as N source.

The Impact of Diferent Vertical Difusion Schemes in a Three-Dimensional Oil Spill Model in the Bohai Sea

Vertical transport is critical to the movement of oil spills in seawater. Breaking waves play an important role by developing a well-defined mixing layer in the upper part of the water column. A three-dimensional （3-D） Lagrangian random walk oil spill model was used here to study the influence of sea surface waves on the vertical turbulence movement of oil particles. Three vertical diffusion schemes were utilized in the model to compare their impact on oil dispersion and transportation. The first scheme calculated the vertical eddy viscosity semi-empirically. In the second scheme, the vertical diffusion coefficient was obtained directly from an Eulerian hydrodynamic model （Princeton Ocean Model, POM2k） while considering wave- caused turbulence. The third scheme was formulated by solving the Langevin equation. The trajectories, percentages of oil particles intruding into water, and the vertical distribution structures of oil particles were analyzed for a series of numerical experiments with different wind magnitudes. The results showed that the different vertical diffusion schemes could generate different horizontal trajectories and spatial distributions of oil spills on the sea surface. The vertical diffusion schemes caused different water-intruding and resurfacing oil particle behaviors, leading to different horizontal transport of oil particles at the surface and subsurface of the ocean. The vertical diffusion schemes were also applied to a realistic oil spill simulation, and these results were compared to satellite observations. All three schemes yielded acceptable results, and those of the third scheme most closely simulated the observed data.

A study of oil spill detection using ASAR images

The oil spilled worldwide causes ecological disasters that result in enormous damages to the quality of marine environment, and great expenses on clear-up operations are needed. Due to its wide coverage and day-night all-weather observation capability, Synthetic Aperture Radar （SAR） is an important tool for oil spill monitoring and detection. C-band SAR is well adapted to detect oil pollution because oil slicks dampen the Bragg waves and reduce radar backscattering coefficients. In order to detect the area of oil slicks, the algorithm consists of these steps： Preprocessing, Masking of land areas, Detection of dark spots, Spot feature extraction, Dark spot classification. In this paper, the authors examined two coastal regions around Hong Kong and Yantai, China. The obtained results performed on Envisat ASAR images have demonstrated that it is efficient to detect oil spill around the coastal regions. The methodology still needs to be refined with the collection of more SAR data in the near future.

The error source analysis of oil spill transport modeling: a case study

Numerical modeling is an important tool to study and predict the transport of oil spills. However, the accu- racy of numerical models is not always good enough to provide reliable information for oil spill transport. It is necessary to analyze and identify major error sources for the models. A case study was conducted to analyze error sources of a three-dimensional oil spill model that was used operationally for oil spill forecast- ing in the National Marine Environmental Forecasting Center （NMEFC）, the State Oceanic Administration, China. On June 4, 2011, oil from sea bed spilled into seawater in Penglai 19-3 region, the largest offshore oil field of China, and polluted an area of thousands of square kilometers in the Bohai Sea. Satellite remote sensing images were collected to locate oil slicks. By performing a series of model sensitivity experiments with different wind and current forcings and comparing the model results with the satellite images, it was identified that the major errors of the long-term simulation for oil spill transport were from the wind fields, and the wind-induced surface currents. An inverse model was developed to estimate the temporal variabil- ity of emission intensity at the oil spill source, which revealed the importance of the accuracy in oil spill source emission time function.

The long-term prediction of the oil-contaminated water from the Sanchi collision in the East China Sea

The condensate and bunker oil leaked from the Sanchi collision would cause a persistent impact on marine ecosystems in the surrounding areas. The long-term prediction for the distribution of the oil-polluted water and the information for the most affected regions would provide valuable information for the oceanic environment protection and pollution assessment. Based on the operational forecast system developed by the First Institute of Oceanography, State Oceanic Administration, we precisely predicted the drifting path of the oil tanker Sanchi after its collision. Trajectories of virtual oil particles show that the oil leaked from the Sanchi after it sank is mainly transported to the northeastern part of the sink location, and quickly goes to the open ocean along with the Kuroshio. Risk probability analysis based on the outcomes from the operational forecast system for years 2009 to2017 shows that the most affected area is at the northeast of the sink location.

Micro- and nanoporous materials capable of absorbing solvents and oils reversibly： the state of the art

Treatment of petroleum spills and organic solvent pollution in general is an important issue; several techniques are under development to remove oil from water. The use of absorbents is one of the most common techniques to tackle this problem. These absorbents can be classified based on their characteristics of recyclability into irreversible and reversible ones. In this review, we discuss the application of several materials as oil absorbents, according to their classification and characteristics such as hydrophobicity, surface area and oil absorption capacity. Also, the fabrication methods for some materials are presented and analyzed.

An analysis of the radar backscatter from oil-covered sea surfaces using moment method and Monte-Carlo simulation: preliminary results

An analysis of the radar backscattering from the ocean surface covered by oil spill is presented using a mi- crowave scattering model and Monte-Carlo simulation. In the analysis, a one-dimensional rough sea sur- face is numerically generated with an ocean waveheight spectrum for a given wind velocity. A two-layered medium is then generated by adding a thin oil layer on the simulated rough sea surface. The electric fields backscattered from the sea surface with two-layered medium are computed with the method of moments （MoM）, and the backscattering coefficients are statistically obtained with N independent samples for each oil-spilled surface using the Monte-Carlo technique for various conditions of surface roughness, oil-layer thickness, frequency, polarization and incidence angle. The numerical simulation results are compared with theoretical models for clean sea surfaces and SAR images of an off-spilled sea surface caused by the Hebei （Hebei province, China） Spirit oil tanker in 2007. Further, conditions for better oil spill extraction are sought by the numerical simulation on the effects of wind speed and oil-layer thickness at different inci- dence angles on the backscattering coefficients.

The influence of Stokes drift on oil spills:Sanchi oil spill case

Spilled oil floats and travels across the water’s surface under the influence of wind,currents,and wave action.Wave-induced Stokes drift is an important physical process that can affect surface water particles but that is currently absent from oil spill analyses.In this study,two methods are applied to determine the velocity of Stokes drift,the first calculates velocity from the wind-related formula based upon a one-dimensional frequency spectrum,while the second determines velocity directly from the wave model that was based on a twodimensional spectrum.The experimental results of numerous models indicated that:(1)oil simulations that include the influence of Stokes drift are more accurate than that those do not;(2)for medium and long-term simulations longer than two days or more,Stokes drift is a significant factor that should not be ignored,and its magnitude can reach about 2%of the wind speed;(3)the velocity of Stokes drift is related to the wind but is not linear.Therefore,Stokes drift cannot simply be replaced or substituted by simply increasing the wind drift factor,which can cause errors in oil spill projections;(4)the Stokes drift velocity obtained from the two-dimensional wave spectrum makes the oil spill simulation more accurate.

Hydrocarbon-Degrading Bacteria and Paraffin from Polluted Seashores 9 Years after the Nakhodka Oil Spill in the Sea of Japan

Pollution of petroleum hydrocarbons, in particular oil spills, has attracted much attention in the past and recent decades. Oil spills influence natural microbial community, and physical and chemical properties of the affected sites. The biodegradation of hydrocarbons by microorganisms is one of the primary ways by which oil spill is eliminated from contaminated sites. One such spill was that of the Russian tanker the Nakhodka that spilled heavy oil into the Sea of Japan on January 2, 1997. The impact of the Nakhodka oil spill resulted in a viscous sticky fluid fouling the shores and affected natural ecosystems. This paper describes the weathering of hydrocarbon-degrading bacteria （genus Pseudomonas） and crystallized organic compounds from the Nakhodka oil spill-polluted seashores after nine years. The Nakhodka oil has hardened and formed crust of crystalline paraffin wax as shown by XRD analysis （0.422, 0.377, and 0.250 nm d-spacing） in association with graphite and calcite after 9 years of bioremediation. Anaerobic reverse side of the oil crust contained numerous coccus typed bacteria associated with halite. The finding of hydrocarbon-degrading bacteria and paraffin wax in the oil crust may have a significant effect on the weathering processes of the Nakhodka oil spill during the 9- year bioremediation.

Detection of oil spill based on CBF-CNN using HY-1C CZI multispectral images

Accurate detection of an oil spill is of great significance for rapid response to oil spill accidents.Multispectral images have the advantages of high spatial resolution,short revisit period,and wide imaging width,which is suitable for large-scale oil spill monitoring.However,in wide remote sensing images,the number of oil spill samples is generally far less than that of seawater samples.Moreover,the sea surface state tends to be heterogeneous over a large area,which makes the identification of oil spills more difficult because of various sea conditions and sunglint.To address this problem,we used the F-Score as a measure of the distance between forecast value and true value,proposed the Class-Balanced F loss function(CBF loss function)that comprehensively considers the precision and recall,and rebalances the loss according to the actual sample numbers of various classes.Using the CBF loss function,we constructed convolution neural networks(CBF-CNN)for oil spill detection.Based on the image acquired by the Coastal Zone Imager(CZI)of the Haiyang-1C(HY-1C)satellite in the Andaman Sea(study area 1),we carried out parameter adjustment experiments.In contrast to experiments of different loss functions,the F1-Score of the detection result of oil emulsions is 0.87,which is 0.03–0.07 higher than cross-entropy,hinge,and focal loss functions,and the F1-Score of the detection result of oil slicks is 0.94,which is 0.01–0.09 higher than those three loss functions.In comparison with the experiment of different methods,the F1-Score of CBF-CNN for the detection result of oil emulsions is 0.05–0.12 higher than that of the deep neural networks,supports vector machine and random forests models,and the F1-Score of the detection result of oil slicks is 0.15–0.22 higher than that of the three methods.To verify the applicability of the CBF-CNN model in different observation scenes,we used the image obtained by HY-1C CZI in the Karimata Strait to carry out experiments,which include two studies areas(study area 2 and study area 3).The experimental results show that the F1-Score of CBF-CNN for the detection result of oil emulsions is 0.88,which is 0.16–0.24 higher than that of other methods,and the F1-Score of the detection result of oil slicks is 0.96–0.97,which is 0.06–0.23 higher than that of other methods.Based on all the above experiments,we come to the conclusions that the CBF loss function can restrain the influence of oil spill and seawater sample imbalance on oil spill detection of CNN model thus improving the detection accuracy of oil spills,and our CBF-CNN model is suitable for the detection of oil spills in an area with weak sunglint and can be applied to different scenarios of CZI images.

Oil spill detection by a support vector machine based on polarization decomposition characteristics

Marine oil spills have caused major threats to marine environment over the past few years.The early detection of the oil spill is of great significance for the prevention and control of marine disasters.At present,remote sensing is one of the major approaches for monitoring the oil spill.Full polarization synthetic aperture radarc SAR data are employed to extract polarization decomposition parameters including entropy（H） and reflection entropy（A）.The characteristic spectrum of the entropy and reflection entropy combination has analyzed and the polarization characteristic spectrum of the oil spill has developed to support remote sensing of the oil spill.The findings show that the information extracted from（1-A）×（1-H） and（1-H）×A parameters is relatively evident effects.The results of extraction of the oil spill information based on H×A parameter are relatively not good.The combination of the two has something to do with H and A values.In general,when H〉0.7,A value is relatively small.Here,the extraction of the oil spill information using（1-A）×（1-H） and（1-H）×A parameters obtains evident effects.Whichever combined parameter is adopted,oil well data would cause certain false alarm to the extraction of the oil spill information.In particular the false alarm of the extracted oil spill information based on（1-A）×（1-H） is relatively high,while the false alarm based on（1-A）×H and（1-H）×A parameters is relatively small,but an image noise is relatively big.The oil spill detection employing polarization characteristic spectrum support vector machine can effectively identify the oil spill information with more accuracy than that of the detection method based on single polarization feature.