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.

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.

Research on the risk-based model for regional emergency resource allocation for ship-source oil spill

The key point for rational allocation of emergency resources is to match the oil spill response capacity with the risk of oil spill. This paper proposes an innovative risk-based model for quantitative regional emergency resource allocation, which comprehensively analyzes the factors such as oil spill probability, hazard consequences, oil properties, weathering process and operation efficiency, etc. The model calculates three major resources, i.e., mechanical recovery, dispersion and absorption, according to the results of risk assessment. In a field application in Xiaohu Port, Guangzhou, China, and the model achieved scientific and rational allocation of emergency resources by matching the assessed risk with the regional capacity, and allocating emergency resources according to capability target. The model is considered to be beneficial to enhancing the resource efficiency and may contribute to the planning of capacity-building programs in high-risk areas.

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.

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.

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.

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 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 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.

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.

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.

Application of computational fluid dynamics simulation for submarine oil spill

Computational fluid dynamics （CFD） codes are being increasingly used in the simulation of submarine oil spills. This study focuses on the process of oil spills, from damaged submarine pipes, to the sea surface, using numerical models. The underwater oil spill model is developed, and a description of the governing equations is proposed, along with modifications required for the particalization of the control volume. Available experimental data were introduced to evaluate the validity of the CFD predictions, the results of which proved to be in good agreement with the experimental data. The effects of oil leak rate, leak diameter, current velocity, and oil density are investigated, by the validated CFD model, to estimate the undersea leakage time, the lateral migration distance, and surface diffusion range when the oil reaches the sea surface. Results indicate that the leakage time and lateral migration distance increase with decreasing leak rates and leak diameter, and increase with increasing current velocity and oil density. On the other hand, a large leak diameter, high density, high leak rate, or fast currents result in a greater surface diffusion range. The findings and analysis presented here will provide practical predictions of oil spills, and guidance for emergency rescues.

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.

Modeling and analysis of a catastrophic oil spill and vapor cloud explosion in a confined space upon oil pipeline leaking

Oil spill-induced vapor cloud explosions in a confined space can cause catastrophic consequences.In this work,investigation was conducted on the catastrophic pipeline leak,oil spill,and the resulting vapor cloud explosion accident occurring in China in 2013 by modeling analysis,field surveys,and numerical simulations.The total amount of the spilled oil was up to2044.4 m3 due to improper disposal.The long residence time of the oil remaining in a confined space permitted the formation of explosive mixtures and caused the vapor cloud explosion.A numerical model was developed to estimate the consequence of the explosion based on volatilization testing results.The results show that the death-leading zone and the glass-breaking zone could be 18 m and 92 m,respectively,which are consistent with the field investigation.The severity of the explosion is related to the amount of the oil spill,properties of oil,and volatilization time.It is recommended that a comprehensive risk assessment be conducted to analyze the possible consequences upon oil spilling into a confined space.Prompt collection and ventilation measures should be taken immediately after the spill occurs to reduce the time for oil volatilization and prevent the mixture from reaching its explosive limit.

Analysis of impacting factors on polarimetric SAR oil spill detection

Polarimetric synthetic aperture radar （SAR） oil spill detection parameters conformity coefficient （μ）, Muller matrix parameters （｜C｜,B0 ）, the eigenvalues of simplified coherency matrix （λnos） and the influence of SAR observing parameters, ocean environment and noise level are investigated. Radarsat-2 data are used to make systematic analysis of polarimetric parameters for different incidences, wind speeds, noise levels and the ocean phenomena （oil slick and look likes）. The influence of the SAR observing parameters, the ocean environment and the noise level on the typical polarimetric SAR parameter conformity coefficient has been analyzed. The results indicate that conformity coefficient cannot be simply used for oil spill detection, which represents the image signal to the noise level to some extent. When the signals are below the noise level for the oil slick and the look likes, the conformity coefficients are negative; while the signals above the noise level corresponds to positive conformity coefficients. For dark patches （low wind and biogenic slick） with the signal below the noise, polarization features such as conformity coefficient cannot separate them with oil slick. For the signal above the noise, the oil slick, the look likes （low wind and biogenic slick） and clean sea all have positive conformity coefficients, among which, the oil slick has the smallest conformity coefficient, the look likes the second, and the clean sea the largest value. For polarimetric SAR data oil spill detection, the noise plays a significant role. So the polafimetric SAR data oil spill detection should be carried out on the basis of noise consideration.

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.

The polarimetric features of oil spills in full polarimetric synthetic aperture radar images

Compared with single-polarized synthetic aperture radar （SAR） images, full polarimetric SAIl images contain not only geometrical and backward scattering characteristics, but also the polarization features of the scattering targets. Therefore, the polarimetric SAR has more advantages for oil spill detection on the sea surface. As a crucial step in the oil spill detection, a feature extraction directly influences the accuracy of oil spill discrimination. The polarimetric features of sea oil spills, such as polarimetric entropy, average scatter angle, in the full polarimetric SAR images are analyzed firstly. And a new polarimetric parameter P which reflects the proportion between Bragg and specular scattering signals is proposed. In order to investigate the capability of the polarimetric features for observing an oil spill, systematic comparisons and analyses of the multipolarization features are provided on the basis of the full polarimetric SAR images acquired by SIR-C/X-SAR and Radarsat-2. The experiment results show that in C-band SAR images the oil spills can be detected more easily than in L-band SAR images under low to moderate wind speed conditions. Moreover, it also finds that the new polarimetric parameter is sensitive to the sea surface scattering mechanisms. And the experiment results demonstrate that the new polarimetric parameter and pedestal height perform better than other polarimetric parameters for the oil spill detection in the C-band SAR images.

Laboratory Investigation into the Evaporation of Natural-Gas Condensate Oils: Hints for the Sanchi Oil Spill

The Sanchi oil tanker collision in the East China Sea on January 6th, 2018 has caused worldwide attention due to its uniqueness. A considerable amount of highly volatile natural-gas condensate oil was spilled, burned and sank with the Sanchi tanker, this entirely new kind of maritime disaster has posed massive unknowns to the public. In this study, for better understanding of the evaporative behavior of condensate oils, two condensate oils were investigated under various laboratory conditions. The overall result demonstrates that the evaporation of condensate oils is highly dependent on the air-exposed time and the total loss of condensate oils could be more than 90% within a short time. However, a certain amount of the high-molecular weight and toxic oil contents such as phenanthrenes still highly remain in the aquatic system even after a long evaporation process, indicating their detrimental potentials to the aquatic organisms. Based on these data, for the Sanchi oil spill accident, it is assumed that although the evaporation weathering of the total condensate oil mass is probably tremendous, the long-term ecological risks of the remaining oil components in the marine environment are strongly recommended to be carefully evaluated.