Oil Spill Trajectory Research Articles

Strategic location model for oil spill response vessels (OSRVs) considering oil transportation and weather uncertainties

In the event of oil spills in offshore oil and gas projects, containment and dispersion equipment must be sent to the affected areas within a critical time by vessels known as oil spill response vessels (OSRVs). Here, we developed an optimization tool, integrated with an oil spill trajectory simulation model, both in deterministic and stochastic alternatives, to support decision-making during the strategic planning of OSRV operations. The tool was constructed in Python using GNOME for oil spill simulations and the GUROBI to solve the optimization model. The tool was applied to a case study in Brazil and afforded relevant recommendations. In terms of research contributions, we proved the viability of the integration between oil spill simulation and mathematical modeling for OSRV strategic operation planning, we explored the stochasticity of the problem with an innovative strategy and we demonstrated flexibility and easy applicability of the framework on real operations.

Mapping pollution dynamics: utilizing GNOME to model oil spill trajectories in tanker terminals.

The aim of this study is to uncover the multifaceted environmental threats posed by Oil Spill Water Pollution (OSWP) originating from tanker terminals situated in the Qeshm and Hormozgan regions of Iran. In this region, water pollution arises from diverse sources, mostly from ruptured pipelines, corroded valves, unforeseen accidents, and aging facilities. The Qeshm Canal and Qeshm Tanker Terminal emerged as pivotal sites for investigation within this study. The focus is directed towards pinpointing vulnerable areas at risk of water contamination and delving into the intricate pathways and impacts associated with oil spills. Utilizing the sophisticated modeling capabilities of the National Oceanic and Atmospheric Administration's (NOAA) GNOME model, the research explores various scenarios extrapolated from seasonal atmospheric and oceanic data through 2022. The findings show the OSWP hazard zones located northeast of Qeshm. Notably, the wind and currents greatly affect how OSWPs are destined and dispersed. This underscores the intricate interplay between environmental factors and spill dynamics. In essence, this study not only sheds light on the imminent environmental threats posed by OSWP but also underscores the critical need for proactive measures and comprehensive strategies to mitigate the adverse impacts on marine ecosystems and coastal communities.

Real-time quality assurance and quality control for a high frequency radar network

This paper recommends end to end quality assurance methods and quality control tests for High Frequency Radar Networks. We focus on the network that is operated by the Mid Atlantic Regional Association Coastal Ocean Observing System (MARACOOS). The network currently consists of 38 radars making real-time measurements of the surface currents over the continental shelf for a variety of applications including search and rescue planning, oil spill trajectory modelling and providing a transport context for marine biodiversity observing networks. MARACOOS has been delivering surface current measurements to the United States Coast Guard (USCG) since May 2009. Data quality is important for all applications; however, since the USCG uses this surface current information to plan life-saving missions, delivery of the best quality data is crucial. We have mapped the components of the HF radar data processing chain onto the data levels presented in the NASA Earth Science Reference Handbook and have applied quality assurance and quality control techniques at each data level to achieve the highest quality data. There are approximately 400 High Frequency radars (HFRs) deployed globally and the presented techniques can provide a foundation for data quality checks and standardization of the data collected by the large number of systems operating today.

Extraction of persistent lagrangian coherent structures for the pollutant transport prediction in the Bay of Bengal

Lagrangian Coherent Structures (LCS) are the hidden fluid flow skeletons that provide meaningful information about the Lagrangian circulation. In this study, we computed the monthly climatological LCSs (cLCS) maps utilizing 24 years (1994–2017) of HYbrid Coordinate Ocean Model (HYCOM) currents and ECMWF re-analysis winds in the Bay of Bengal (BoB). The seasonal reversal of winds and associated reversal of currents makes the BoB dynamic. Therefore, we primarily aim to reveal the cLCSs associated with seasonal monsoon currents and mesoscale (eddies) processes over BoB. The simulated cLCS were augmented with the complex empirical orthogonal functions to confirm the dominant lagrangian transport pattern features better. The constructed cLCS patterns show a seasonal accumulation zone and the transport pattern of freshwater plumes along the coastal region of the BoB. We further validated with the satellite imagery of real-time oil spill dispersion and modelled oil spill trajectories that match well with the LCS patterns. In addition, the application of cLCSs to study the transport of hypothetical oil spills occurring at one of the active oil exploration sites (Krishna-Godavari basin) was described. Thus, demonstrated the accumulation zones in the BoB and confirmed that the persistent monthly cLCS maps are reasonably performing well for the trajectory prediction of pollutants such as oil spills. These maps will help to initiate mitigation measures in case of any occurrence of oil spills in the future.

Risk Assessment of Oil Spills along the Coastline of Jiaozhou Bay Using GIS Techniques and the MEDSLIK-II Model

With the increasing global reliance on maritime oil transportation, oil spills pose significant environmental hazards to coastal ecosystems. This study presents a comprehensive quantitative framework for assessing oil spill risks along the Jiaozhou Bay coastline in China. The research begins with an analysis of historical spill data to construct representative oil spill simulation scenarios. The advanced MEDSLIK-II oil spill prediction model is then employed to simulate oil spill trajectories under these scenarios, focusing on key parameters such as oil thickness and mass to evaluate the hazard levels associated with each scenario. Subsequently, the Environmental Sensitivity Index (ESI) is utilized to assess the vulnerability of coastal zones, while Geographic Information System (GIS) techniques are employed for a spatial analysis and visualization of the results. The case study, covering a 26.87 km stretch of the Jiaozhou Bay coastline, reveals 10 high-risk zones with a total length of 8561.2 m. These areas are predominantly characterized by saltwater marshes, brackish water marshes, and inundated low-lying areas, with ESI rankings of 9 and 10, accounting for 24% of the 339 analyzed segments. The modeling results indicate that in the simulated scenarios, oil spills originating from the Huangdao Oil Port and Qianwan Port pose the greatest risks, with potential impacts extending up to 12 km and 15 km along the coastline, respectively. The study highlights the importance of considering multiple factors, including oil spill trajectories, coastal geomorphology, and ecological sensitivity, in comprehensive risk assessments. The proposed framework demonstrates potential for adaptation and application to other coastal regions facing similar oil spill risks, contributing to the advancement of coastal management practices worldwide.

OIL SPILL SIMULATION IN THE BALI STRAIT USING THE GNOME AND FVCOM MODELS ON EASTERLY SEASON

Among several forms of marine pollution, oil damages coastal ecosystems. Repeated reports of oil contamination in the marine environment can partly load with major shipping lines. The Ketapang-Gilimanuk crossing over the Bali Strait is Indonesia's second busiest ferry port after Merak-Bakauheni. The most congested shipping routes can carry a significant risk of environmental damage from an oil spill. Oil spill trajectory modelling is carried out to reduce the impact of this possible disaster. Therefore, the use of modelling to ascertain the route of the oil spill was considered. The oil leak path is simulated using the GNOME model. Two oil spill scenarios were used as input models. The chosen location is around the Ketapang Gilimanuk crossing, as well as the time of the easterly season. An ocean HF radar stationed in the Bali Strait verifies the accuracy of the current marine data generated by FVCOM. To see the pattern of the oil spill trajectory based on a ten days simulation, we combined the latest data from FVCOM with GNOME. To determine the ability of the model to predict the flow and trajectory of oil spills in the Bali Strait, this study try to analyze and interpret the oil spill trajectory from model and then validate the model results with satellite imagery.
 Keywords: Bali strait; oil spill; trajectory; GNOME; FVCOM; HF Radar

Stochastic assessment of oil spill trajectory: a case study Paradeep Offshore, Odisha

Stochastic assessment of oil spill trajectory: a case study Paradeep Offshore, Odisha

Oil spill trajectory modeling and validation: case study on a marine incident at Adriatic Sea

Oil spill trajectory modeling and validation: case study on a marine incident at Adriatic Sea

Modeling the Agia Zoni II tanker oil spill in Saronic Gulf, Greece

We employed GNOME to simulate the oil spill due to the sinking of the tanker “Agia Zoni ΙΙ” in September 2017 in Saronic Gulf. We performed simulations using various combinations of wind and current input, and values of the GNOME parameters, and compared the simulated oil spill trajectories with coastal pollution and satellite data. The best scenario, i.e., the combination that showed the most satisfactory agreement with field data, uses wind data from one of the closest meteorological stations, calculated currents by a hydrodynamic model and default values of the parameters, except for the windage and the refloat half-life whose proposed values are 3–4 % and 6 h, respectively. Neglecting the effect of the wind in the best scenario worsened the agreement. Mass balance results depicted that approximately 47 % of the total 500 tons of the oil spill ended up on the coastline of Attica peninsula and Salamina Island.

Simulation of Oil Spills in Inland Rivers

The shipping volume in inland waterways has been rapidly increasing in recent years. However, it is still challenging to trace oil spills caused by maritime accidents. In this study, the oil spill dispersion trajectory in inland rivers was obtained by simulating the trajectory of oil particles under different waterway conditions based on a simulated flow field. Firstly, the flow field was simulated using a volume of fluid (VOF) model and the solution of an open-channel equation. Then, an oil particle diffusion and drift model was established using Python to simulate the diffusion of the oil. Finally, eight oil spill simulation scenarios were conducted with different channel shapes and cross-sections. The results showed that oil spills spread more extensively in a curved channel with a trapezoidal cross-section compared to other channel shapes and cross-sections. The findings of this research could be used to guide inland river environmental protection and oil spill trajectory tracking.

Oil Discharge Trajectory Simulation at Selected Baltic Sea Waterway under Variability of Hydro-Meteorological Conditions

The paper deals with an important issue related to the identification, modelling, and prediction of environmental pollution in aquatic ecosystems of the Baltic Sea caused by anthropopressure. Water ecosystems are in danger nowadays because of the negative influence of chemical releases in seas, oceans, or inland waters. The crucial issue is to prevent the oil spills and mitigate their consequences. Thus, there is a need for methods capable of reducing the water pollution and enhancing the effectiveness of port and marine environment preservation. The challenge in implementing actions to remove and prevent horizontal oil discharge lies in accurately determining its shape and direction of oil spreading. The author employed a self-designed software utilizing modified and developed mathematical probabilistic models to forecast the movement and dispersion of an oil spill in diverse hydrological and meteorological conditions. This involved determining the trajectory and movement of a spill domain, which consists of elliptical sub-domains undergoing temporal changes. The research results obtained are the initial results in the oil spill simulation problem. This approach represents an expanded and innovative method for determining the spill domain and tracking its movement, applicable to oceans and seas worldwide. It expands upon the methodologies firstly discussed, thereby broadening the range of available techniques in this field. A simple model of an oil spill trajectory simulation and a surface oil slick as an ellipse is illustrated using a time-series of selected hydro-meteorological factors that change at random times. The author proposes a Monte Carlo simulation method to determine the extent of an oil spill in an aquatic ecosystem, taking into account the influence of varying hydro-meteorological conditions. A semi-Markov model is defined to capture the dynamics of these conditions within the spill area and develop an enhanced algorithm for predicting changes in the shape and movement of the spill domain under changing these conditions. By applying the algorithm, a simulation is conducted to provide short-term prediction of the oil discharge trajectory in a selected Baltic Sea waterway. To enhance the accuracy of predicting the process of changing conditions, uniformly tested joint datasets from the open sea water area were incorporated. Finally, the potential future prospects and directions for further research in this field are discussed.

Simulation of Oil Spill Trajectory and Fate at the Southern Entrance of the Suez Canal, Red Sea, Egypt

The Suez Canal suffers from heavy maritime traffic, especially oil tankers, due to its strategic location between the Mediterranean and the Red Sea. As a result, it is prone to accidental oil spills, which might obstruct the maritime lane via the canal and severely harm the marine and coastal ecosystems. This study aims to forecast an oil spill trajectory and fate under the influence of different wind regimes using the General NOAA Operational Modeling Environment (GNOME) and the Automated Data Inquiry for Oil Spills (ADIOS2) models to define the potentially affected regions. Hence, four scenarios were simulated, assuming a spill of one thousand metric tons of Arabian light crude oil into the seawater about two kilometers from the Suez Canal’s southern entrance. The results highlight that wind direction and sea currents substantially affect the movement of oil spills. The trajectory maps show that the north-west wind forces the spilled oil to move toward the southeast direction, threatening the navigation lane through the Suez Canal and about 38 km of beaches south of the canal, which has several vital projects such as the Ayoun Mousse power plant and a lot of resorts. In the case of northern winds, the oil moved south in the center of the Gulf, which may allow response teams more time to clean up the spill. However, in the case of north-east winds, the oil drifted southwesterly and threatened the Green Island and western shores of the Gulf, which has many tourist villages. About a quarter of the oil evaporated, and more than two-thirds of the oil emulsified in all four scenarios. For the first time, this study has provided an understanding of oil spill forecasting and trajectory modeling for the Suez Canal’s southern entrance. Also, it can be considered a prediction tool for Egypt’s policymakers and Suez Canal Authority (SCA) to develop adequate and practical strategies to mitigate crude oil spill consequences.

Tracing the impact and recovery trajectory of oil spill affected tropical rocky intertidal macrobenthic communities using the BOPA index

A yearlong study was conducted to assess the impact of an oil spill on macrobenthos of rocky intertidal zone of Uran, India and its recovery processes, by comparing impacted site with a reference. Immediate acute effects observed were elevated sediment hydrocarbons, absence of macroalgae and amphipods, mass mortality of macrofauna and dominance of the opportunistic nereid, Namalycastis senegalensis. As the hydrocarbons reduced at the impacted site by ~50 % within three months, gradual re-appearance of macroalgae and re-colonization of amphipods (51.4 %) and sensitive polychaetes (7 %) indicated that the recovery was well underway. The amphipod, Allomelita pellucida proved to be a potential indicator of oil contamination. BOPA correlated with sediment hydrocarbons and performed effectively as the extant macrobenthic communities had sufficient representation of Polychaeta and Amphipoda. Notwithstanding the distinct initial impacts of the oil spill, comparable macrobenthic assemblages comprised of sensitive species at both sites after a year confirmed complete recovery.

Improved prediction of oil drift pattern using ensemble of ocean currents

ABSTRACT Indian Coast Guard and oil spill responders utilise the operational oil spill advisory services of the Indian National Centre for Ocean Information Services (INCOIS) during the event of oil spills for setting up spill response operations. Oil drifts in marine zones are dominated by ocean currents. Ocean currents generated by numerical models have errors and uncertainties due to model approximations, inaccurate initial and boundary conditions in the model setup. An attempt was made to generate an oil spill advisory using a weighted ensemble of ocean currents. In this study, the oil spill trajectory model, General National Oceanic and Atmospheric Administration (NOAA) Operational Modeling Environment (GNOME) was forced using a weighted ensemble of ocean currents for the Heavy Furnace Oil (HFO) spill reported off Ennore port during 0400 hours (IST) of 28 January 2017. The inverse-variance weighting method was used to estimate weights by comparing zonal and meridional components of individual model ocean currents, with that of High Frequency (HF) Radar currents. The zone of HFO spread obtained while using an ensemble of ocean currents was compared with oil slick signatures obtained from Synthetic Aperture Radar (SAR) data on 0600 hours (IST) of 29 January 2017. It was noted that the trajectory patterns obtained from the weighted ensemble of ocean currents were well within the observed zone of oil slicks, compared to that of individual model ocean currents.

Prediction model and consequence analysis for riverine oil spills

Long-distance oil and gas pipelines play an important role in ensuring energy imports, but can cause riverine oil spills and threaten public health and the environment. The emergency disposal of spilled oil is affected by a number of factors such as the difficulty of disposal and the long recovery cycle; however, there are deficiencies in the understanding of river oil spills. In this study, a prediction model of the river oil spill trajectory based on the random walk particle tracking algorithm was constructed. The performance of the model was tested by simulating the Enbridge Line 6B Oil Discharge scenario occurred in the United States in 2010. The temporal and spatial variations of the oil pollution zone in downstream and vertical directions were studied, and the interception effects on the arrival time of oil in key sections were obtained. Results showed that after the spilled oil entered the surface water body, the tiny oil droplets generated by crushing can remain underwater for a long time, making them difficult to detect and intercept. It can further combine with suspended particles in the water, settle, and pollute the riverbed, which has a greater potential for harm and risk. The model offers helpful information for the first-phase emergency response for riverine oil spills.

Modeling marine oil spill trajectory and fate off Hurghada, Red Sea coast, Egypt

Modeling marine oil spill trajectory and fate off Hurghada, Red Sea coast, Egypt

Modelling and CFD simulation of the trajectory of an oil spill in a large domain: Analysis of the 2003 Foss Barge — Point Wells event

This work proposes a procedure for the Computational Fluid Dynamics (CFD) simulation of an oil spill at a large domain. The use of CFD in a large domain usually has restrictions due to the discretization that is needed for good accuracy. The problem increases as the wind effects over a wavy sea surface must be taken into account. To overcome these difficulties, these effects are included in the boundary conditions, through analytical models or simplified simulations. The effect of the wind is commonly determined by a wind drift factor that estimates the wind induced sea surface velocity as a percentage of the wind speed. In this paper, rather than using fixed or random values for the wind drift factor, a methodology based on CFD simulations of the wind acting over the sea surface is used together with analytical formulations, in order to reduce the subjectivity in its estimation. In addition, to avoid modelling the waves and the air phase, the wind effects are simulated as an equivalent shear stress boundary condition. This procedure is used in the simulation of the Foss Barge — Point Wells oil spill. The results of the oil spill trajectory are compared to the observed trajectory.

Numerical Study on the Influence of Model Uncertainties on the Transport of Underwater Spilled Oil.

Oil pollution influences marine biology, ecology, and regional sustainable development capacity, but model uncertainties limit the ability of the numerical model to accurately predict the transport and fate of the underwater oil spill. Based on a three-dimensional underwater oil spill model validated by satellite images of the oil slick at the sea surface, the Penglai 19-3 oil spill accident in the Bohai Sea was simulated; in addition, several sensitivity experiments were set up to investigate the influence of model uncertainties in the background wind, current, start time of the oil spill, and spill site on the transport of underwater spilled oil in the Penglai 19-3 oil spill accident. The experimental results indicate that the uncertainty in the background wind has a certain impact on the simulated centroid position at the sea surface, and little effect on the simulated underwater results, while the uncertainty in the background current has a significant influence on the transport of the underwater spilled oil both at the sea surface and underwater. An uncertainty of 24 h in the start time of the oil spill can cause more than 1 time larger than the benchmark case displacement of the oil spill centroid point and sweeping area at the sea surface, as the periodic tidal current is the main constituent of the ocean current in the Bohai Sea. The uncertainty in the spill site has a large influence on the final position of the oil spill centroid point, but the oil spill trajectories do not intersect with each other within 48 h, which makes it possible to identify the oil spill platform from the actual observations. The influence of uncertainties in the important model inputs and key model parameters on the transport of underwater spilled oil in the Penglai 19-3 oil spill accident is evaluated for the first time, which is of substantial significance for improving the prediction accuracy of the transport and fate of underwater oil spills.

Estimating potential oil spill trajectories and coastal impacts from near-shore storage facilities: A case study of FSO Nabarima and the Gulf of Paria

The FSO Nabarima is a floating storage facility and offloading vessel in the Gulf of Paria, between Venezuela and the island of Trinidad. During the latter half of 2020, the Nabarima was disabled, holding approximately 1.3 million barrels (55 million gallons) of crude oil onboard. In October 2020, the vessel was tilting and potentially at risk of spilling its payload into open water. Although all of the oil on the Nabarima was successfully offloaded by April 2021, the threat of large crude oil releases is ubiquitous and persistent in many coastal regions, threatening local ecosystems and livelihoods in coastal communities. This paper aims to highlight a framework for evaluating the potential spatial vulnerability of coastlines should oil be released from near-shore storage facilities. We use the Nabarima as a broadly representative case study and simulate a range of potential spills through space and time to highlight coastal vulnerabilities in the region. The results suggest strong spatiotemporal variability in spill behavior and impact(s) throughout the Gulf of Paria. In addition, we detail potential spill cleanup and mitigation strategies and discuss the challenges of coordinating cross-national responses to these types of spill scenarios.

Applying finite-time lyapunov exponent to study the tidal dispersion on oil spill trajectory in Burrard Inlet

This study used a combination of Finite-Time Lyapunov Exponent (FTLE) values, residual currents, and tidal excursion lengths to systematically investigate the effects of tidal dispersion on oil spill trajectories in Burrard Inlet, BC, Canada, which is a tidally dominated estuary. The FTLE analysis results showed that tidal type and tidal phase significantly influenced the FTLE fields because the flow structure and the location of saddle points varied as a function of the tidal type and tidal phase. Some transport barriers formed in the Inner Harbour, which blocked the water exchange between the western and eastern parts of the inlet. Moreover, tidal mixing in the wider regions of Burrard Inlet (i.e., the western Outer Harbour) was relatively weak than in the narrower areas (i.e., First Narrows and Second Narrows). The observations from the FTLE analysis agreed well with the residual currents and tidal excursion results. The drifter trajectories were consistent with the Lagrangian coherent structure lines extracted from the FTLE analysis. To verify the tidal dispersion impact on an oil spill trajectory in the inlet, the FTLE fields were compared with a real oil spill that occurred in Burrard Inlet in 2015 (the M/V Marathassa oil spill). The FTLE fields reasonably explained the spilled oil’s trajectories from the real event. In addition, a set of stochastic oil spill models were run in this study and found that the FTLE analysis was a reliable tool for oil spill tracking. Overall, the FTLE method would be a valuable addition to practical oil spill response planning.