Maritime Oil Research Articles

Spatial and Temporal Variations in Offshore Crude Oil Transportation: Insights From China's Coastal Ports

ABSTRACTAnalyzing the spatial and temporal variations of offshore crude oil transportation at China's coastal ports is critical for the country's energy security. The automatic identification system provides high‐resolution real‐time data on China's offshore crude oil transportation, offering more precise spatial and temporal insights than existing statistical studies. In this study, we propose a novel method for calculating offshore crude oil transportation volumes by considering the operational status of crude oil tankers as “empty” or “full.” This approach enhances reliability and provides detailed port‐level transport data. Our findings reveal notable similarities between the centrality measures of maritime oil transportation and oil tanker networks, but significant differences in community divisions. Specifically, in the tanker networks, Chinese ports are categorized into three regions, with one region being dominant and the other two regions containing only four ports. In contrast, the oil flow networks show China divided into two major regions and two minor ones. This study offers valuable contributions to strengthening energy security in China and supports informed policy development and implementation.

Marine Radar Oil Spill Detection Method Based on YOLOv8 and SA_PSO

In the midst of a rapidly evolving economic landscape, the global demand for oil is steadily escalating. This increased demand has fueled marine extraction and maritime transportation of oil, resulting in a consequential and uneven surge in maritime oil spills. Characterized by their abrupt onset, rapid pollution dissemination, prolonged harm, and challenges in short-term containment, oil spill accidents pose significant economic and environmental threats. Consequently, it is imperative to adopt effective and reliable methods for timely detection of oil spills to minimize the damage inflicted by such incidents. Leveraging the YOLO deep learning network, this paper introduces a methodology for the automated detection of oil spill targets. The experimental data pre-processing incorporated denoise, grayscale modification, and contrast boost. Subsequently, realistic radar oil spill images were employed as extensive training samples in the YOLOv8 network model. The trained detection model demonstrated rapid and precise identification of valid oil spill regions. Ultimately, the oil films within the identified spill regions were extracted utilizing the simulated annealing particle swarm optimization (SA-PSO) algorithm. The proposed method for offshore oil spill survey presented here can offer immediate and valid data support for regular patrols and emergency reaction efforts.

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.

On global maritime oil piracy: an association rules analysis

AbstractMaritime piracy is a global problem that disrupts oil flows and products. This research attempts to identify potential association rules between the features of hostile acts against tankers. To that end, the Apriori algorithm is used. We use data from the National Geospatial-Intelligence Agency and modify them in a basket case style. Essential features of an attack are examined, such as the closeness to the coasts, the cruising status of the tankers, and the time neighboring other attacks. Despite the perception we have of them, it turns out that pirates follow conservative strategies. It is found that success is strongly coupled with the safety of the attack by striking near the coast and on anchored tankers. The produced association rules include different time-neighboring conditions and no values regarding the attack month. This implies no strong preference for starting an attack, close or far from a previous episode, and no seasonality.

A REVIEW OF INTERNATIONAL CONVENTIONS REGARDING THE RESPONSIBILITIES CAUSED BY OIL POLLUTION OF THE SEAS

The goal of this study was to thoroughly evaluate international conventions concerning the responsibilities caused by oil pollution in marine environment The research takes an analytical-descriptive approach, with a detailed analysis of relevant literature and research in this topic. The findings emphasize the importance of thorough environmental control across all stages of offshore oil and gas resource development, including exploration, production, transportation, and relocation. Inadequate management of oil and gas leaks in saltwater causes pollution, resulting in severe environmental consequences and eventual accountability. Such responsibility takes the form of both pollution control, and in cases of negligence, civil liability imposed on polluters. Notably, international accords addressing duties arising from maritime oil contamination are critical subjects in oil legislation. This article critically examines the provisions of these treaties that relate to oil pollution-related duties in marine ecosystems, as documented in international legal instruments. In conclusion, the research shows that relying solely on the traditional civil liability foundation for marine oil contamination not only fails to compensate for real-world harms but also jeopardies human rights. This undermines the values expressed in international frameworks advocating for a healthy environment, putting future generations' well-being at risk, as outlined in successive international treaties

Assessing the Connectivity Reliability of a Maritime Transport Network: A Case of Imported Crude Oil in China

Crude oil transportation is a vital component of the global energy supply, and the global Crude Oil Maritime Transportation Network (COMTN) plays a crucial role as a carrier for crude oil transportation. Once the network faces attacks that result in the failure of certain routes, a severe threat is posed to the crude oil supply security of importing countries. Therefore, it is crucial to evaluate the reliability of the COMTN. This study proposes a model for evaluating the reliability of the imported COMTN by analyzing the impact of node failures. Firstly, the network is constructed using complex networks (CNs) theory, with ports, canals, and straits as nodes, and shipping routes as directed edges. Secondly, based on the Weighted Leader Rank algorithm, a comprehensive evaluation metric for CNs is established, and a node importance assessment model is developed to rank the nodes accordingly. Thirdly, a case study is conducted using China’s imported COMTN as an example, evaluating the connectivity reliability (CR) under random and deliberate attack scenarios. Finally, measures and recommendations are provided to enhance the CR of China’s imported COMTN. The findings indicate that deliberate attacks pose a greater threat, and reliability varies across maritime routes, with the Americas route exhibiting higher reliability compared to the Middle East and Southeast Asia routes. The results of this study can provide relevant recommendations for policy makers. The model proposed in this study can also be applied to other countries and regions to assess the connectivity reliability of their local COMTNs and develop appropriate measures for the results.

The Influence of a Key Indicator kv on the Diffusion Range of Underwater Oil Spill

As oil spills cause harm to the survival and environment of the ocean, the objective of the present paper is to study the oil migration range using the key indicator kv, which is defined as the ratio of oil spill speed to ocean current speed. The correctness of diffusion models created and estimated for subsea oil spills can be verified by experiments. We also considered the effect of key indicators on the horizontal and vertical dispersion ranges of oil spills. The study’s findings show that, under various kv settings, the horizontal and vertical spreading heights of oil spills both increase as kv rises. When kv is equal, the leakage velocity and water flow velocity increase synchronously, and over time, the horizontal distance and vertical diffusion height of the oil spill gradually increase. In the early stages of an oil spill, when kv = 50, 100, or 150, the vertical spreading velocity will rapidly decrease. The vertical spreading speed of spilled oil increases as kv rises when the water flow rate remains constant. The horizontal migration distance grows as kv decreases when the leakage rate is constant. Fitting curves for the vertical rise height and horizontal spreading distance for the same and various kv settings were also obtained in order to anticipate the migration mode of oil spills. This is critical for dealing with environmental damage caused by maritime oil spills, as well as emergency responses.

Emergency fleet scheduling for maritime oil spill accidents considering demand-site dynamic motion under uncertain demand

This paper studies an optimal scheduling method for emergency fleets in maritime oil spill accidents. An oil spill accident has the characteristic of a multipoint distribution of demand sites. Considering the suddenness of the accident and the dynamic motion of oil film at sea, the demand for emergency resources is uncertain and the location of demand sites is time-varying. Through analysis of these characteristics, an emergency fleet scheduling model with multi-centre and multi-demand points was established. The study considered the demand uncertainty of emergency resources and the time-varying location of the demand sites to minimise emergency transportation costs and environmental pollution losses. Accordingly, an improved hybrid metaheuristic algorithm was designed based on a genetic algorithm and a simulated annealing algorithm. Numerical experiments were conducted to verify the effectiveness and practicability of the proposed method. The results can provide decision-making reference for the emergency response to maritime oil spill accidents.

Reducing Russia’s Oil Revenues

On 5 December 2022, the EU, US and other G7 states imposed a price cap on Russian maritime oil shipments to help reduce income to the Kremlin while protecting the West’s energy supplies. Jan Stockbruegger assesses this experimental sanction and analyses the logic behind it, key findings so far and how policies could be improved to better enforce the cap.

Researching Offshore Facilities and Choosing an Appropriate Platform for Hydrate Extraction in the Bay of Bengal

Offshore buildings are used in various locations and sea depths for several reasons. Different equipment, platforms, and design techniques are needed depending on water depth, climatic conditions, structural arrangement, and new concepts. Offshore constructions usually generate and transport oil, gas, and other commodities. Bangladesh has yet to use the Bay of Bengal's hydrocarbon potential for oil and gas. Bangladesh lags behind India and Myanmar in maritime oil and gas discovery. In 50 years, Bangladesh's sea barriers have yielded no benefits. Bangladesh's economy is hindered by its high crude oil imports. Focus on offshore petroleum exploration to locate "black gold" now. Therefore, an offshore structure is needed. This thesis paper covers the fundamentals of all offshore systems, broadens the research, and recommends appropriate platforms for various sea-water depths, which those platforms are meant to be built for hydrates predicted in the Bay of Bengal. The paper uses the Bay of Bengal sedimentation and estimated water depth to choose offshore constructions. The country's maritime boundaries have 26 oil and gas blocks. There are 11 in shallow water and 15 in deep sea. According to statistics, the blocks are on the continental shelf and deep-water region. Five zones make up the Bay of Bengal continental shelf. They are shores A-B, B-C, C-D, D-E, and E-F after region F continental slope continues till the deep sea area. The continental slope zone C-D has 64-106 m water depth. Therefore, the Bay of Bengal continental shelf is suitable for all permanent offshore buildings except this zone. Only concrete gravity platforms fit this zone. We need the technology to search for oil and gas in water. It takes a lot of work to get foreign companies to work together. Thus, skilled people should work on it and encourage government or private businesses to develop oil and gas production technology.

ASA-DRNet: An Improved Deeplabv3+ Framework for SAR Image Segmentation

Pollution caused by oil spills does irreversible harm to marine biosystems. To find maritime oil spills, Synthetic Aperture Radar (SAR) has emerged as a crucial mean. How to accurately distinguish oil spill areas from other types of areas is a committed step in detecting oil spills. Owing to its capacity to extract multiscale features and its distinctive decoder, the Deeplabv3+ framework has been developed into an excellent deep learning model in field of picture segmentation. However, in some SAR pictures, there is a lack of clarity in the segmentation of oil film edges and incorrect segmentation of small areas. In order to solve these problems, an improved network, named ASA-DRNet, has been proposed. Firstly, a new structure which combines an axial self-attention module with ResNet-18 is proposed as the backbone of DeepLabv3+ encoder. Secondly, a atrous spatial pyramid pooling (ASPP) module is optimized to improve the network’s capacity of extracting multiscale features and to increase the speed of model calculation and finally merging low-level features of different resolutions to enhance the competence of network to extract edge information. The experiments show that ASA-DRNet obtains the better results compared to other neural network models.

Quantitative ecological risk assessment of oil spills: The case of the Fernando de Noronha Archipelago

The upward trend in maritime oil transport increases the risk of oil spills, which have the potential to cause considerable damage to the marine environment. Therefore, a formal approach to quantify such risks is required. In mid-2010, a conservative Quantitative Ecological Risk Assessment based on population modeling, was performed in the Fernando de Noronha Archipelago. In this research, we enhance a previous assessment using the following models: (i) a Lagrangian approach to perform oil spill simulations, and (ii) the estimated frequency of accidents aggregating databases and expert opinions through a Bayesian-based method. Then, we quantify ecological risks as probabilities of half loss (i.e., 50 % population size decline) of a representative species of the archipelago's ecosystem. The results are summarized into risk categories to be straightforwardly communicated to the general public and provide reliable information that can aid decision-makers in coping with these events.

Multi-product and multi-period maritime oil logistics model with a cooperative approach among hubs

In this paper, the modelling of maritime oil logistics problem in non-cooperative and cooperative approaches is addressed. The problem includes several hubs; each hub has vessels and boats for maritime transport. Rigs are supplied in a time window. In the non-cooperative model, each hub supplies its own rigs. In the cooperative model, it is possible to share resources among hubs. Genetic algorithm (GA) and invasive weed optimisation (IWO) are used as solution approaches. To demonstrate the efficiency of solution methods, 15 numerical examples are designed and the results are compared with GAMS. The results indicate that the IWO algorithm has high efficiency in obtaining near-optimal solutions in a shorter CPU time. Also, cost is decreased significantly when a cooperative approach is applied. Using optimisation models lead to a considerable decrease in expenditures of maritime oil logistics. The proposed model can be widely used for oil and gas companies involved in offshore logistics. [Received: March 21, 2022; Accepted: July 20, 2022].

Multi-product and multi-period maritime oil logistics model with a cooperative approach among hubs

Multi-product and multi-period maritime oil logistics model with a cooperative approach among hubs

Co-blow-spinning of two-phase liquid to build Bead-Curtain fiber substructure for oil adsorption

The development of oil sorbents with special substructure, high adsorption capacity, reusability and good mechanical properties is of great significance for dealing with frequent maritime oil spill incidents and industrial oil-containing wastewater emission. In this work, the polystyrene (PS)/ polyvinylidene fluoride (PVDF) composite fibrous sponges with high oil adsorption capacity were fabricated by constructing a two-phase dispersion system from the microscopic perspective in fiber forming process used co-blow-spinning method. The special Bead-Curtain fiber substructure was obtained due to the difference in the stretching process of the PS and PVDF solution with different viscosity. The precursor solution of the PS/PVDF composite fibrous sponge with PVDF concentration of 20 % (SF2) increased to 79 mPa·s attributed to the addition of PVDF. The SF2 exhibited a high specific surface area (43.418 m2/g), total pore volume (0.4348 cm3/g) and adsorption capacity for various organic solvents (especially up to 279 g/g for motor oil), as well as retaining 159 g/g for motor oil after 10 cycles. Moreover, the addition of PVDF enhanced the mechanical properties of the sponges, whereas the tensile strength of the SF6 sponge was 2.36 times that of the pure PS sponge. The co-blow-spinning of two-phase liquid is a novel strategy for controlling the substructure of fibers from the microscopic perspective, which provides a novel point of view in recycling marine spilled oil.

Influencing factors of crude oil maritime shipping freight fluctuations: a case of Suezmax tankers in Europe–Africa routes

PurposeThe paper aims to identify the contributors to freight rate fluctuations in the Suezmax tanker market; this study selected the refinery output, crude oil price, one-year charter rate and fleet development as the main influencing factors for the market analysis.Design/methodology/approachThe paper used the vector error correction model to evaluate the degree of impact of each influencing factor on Suezmax tanker freight rates, as well as the interplay between these factors.FindingsThe conclusion and results were tested using the 20-year data from 1999 to 2019, and the methodology and theory of this paper were proved to be effective. Results of this study provide effective reference for scholars to find the law of fluctuations in Suezmax tanker freight rates.Originality/valueThis paper provides a decision-making support tool for tanker operators to cope with fluctuation risks in the tanker shipping market.

Long Short-Term Memory and Graph Convolution Network for Forecasting the Crude Oil Traffic Flow

Understanding maritime network structure and traffic flow changes is a challenging task that must incorporate economic, energy, geopolitics, maritime transportation, and network sciences. Crude oil is the most imported energy in the world. Investigating the crude oil maritime network status and predicting the crude oil traffic flow changes has great significance for the global trade, especially for key crude oil importing/exporting regions and countries. To address this, a system-based approach using long short-term memory and graph convolution network for the crude oil traffic flow forecasting named LGCOTFF is introduced. The LGCOTFF approach constructs a maritime transportation network firstly, and then calculates and predicts the node traffic flow based on trajectory data and crude oil berth geographical position. Firstly, we construct a maritime crude oil transportation network based on supply-demand relationship, ship trajectory and route information. Then, we design an approach to calculate how many crude oil ships finished up-load/offtake tasks in a single week for each port, and gather this data to countries and regions. Finally, we design a deep learning neural network named long short-term memory and graph convolution network (L-GCN) to extract the temporal and spatial characteristics of crude oil transportation, and predict the node traffic flow. We evaluate the proposed model on China, Russia, Middle East and America respectively and observe consistent improvement of more than 10% over state-of-the-art baselines.

Association of neighborhood deprivation with pulmonary function measures among participants in the Gulf Long-Term Follow-up Study

IntroductionIndividual-level socioeconomic status (SES) has been shown to be an important determinant of lung function. Neighborhood level SES factors may increase psychological and physiologic stress and may also reflect other exposures that can adversely affect lung function, but few studies have considered neighborhood factors. ObjectiveOur aim was to assess the association between neighborhood-level SES and lung function. MethodsWe cross-sectionally analyzed 6168 spirometry test results from participants in the Gulf long-term Follow-up Study, a large cohort of adults enrolled following the largest maritime oil spill in US history. Outcomes of interest included the forced expiratory volume in 1 s (FEV1; mL), the forced vital capacity (FVC; mL), and the FEV1/FVC ratio (%). Neighborhood deprivation was measured by linking participant home addresses to an existing Area Deprivation Index (ADI) and categorized into quartiles. Individual-level SES measures were collected at enrollment using a structured questionnaire and included income, educational attainment, and financial strain. We used multilevel regression to estimate associations between ADI quartiles and each lung function measure. ResultsGreater neighborhood deprivation was associated with lower FEV1: βQ2vsQ1: −30 mL (95% CI: −97, 36), βQ3vsQ1: −70 mL (95% CI: −135, −4) and βQ4vsQ1: −104 mL (95% CI: −171, −36). FVC showed similar patterns of associations with neighborhood deprivation. No associations with the FEV1/FVC ratio were observed. ConclusionNeighborhood deprivation, a measure incorporating economic and other stressors, was associated with lower FEV1 and FVC, with magnitudes of associations reaching clinically meaningful levels. The impact of this neighborhood SES measure persisted even after adjustment for individual-level SES factors.

Next-Generation Smart Response Web (NG-SRW): An Operational Spatial Decision Support System for Maritime Oil Spill Emergency Response in the Gulf of Finland (Baltic Sea)

The Baltic Sea is a unique and sensitive brackish-water ecosystem vulnerable to damage from shipping activities. Despite high levels of maritime safety in the area, there is a continued risk of oil spills and associated harmful environmental impacts. Achieving common situational awareness between oil spill response decision makers and other actors, such as merchant vessel and Vessel Traffic Service center operators, is an important step to minimizing detrimental effects. This paper presents the Next-Generation Smart Response Web (NG-SRW), a web-based application to aid decision making concerning oil spill response. This tool aims to provide, dynamically and interactively, relevant information on oil spills. By integrating the analysis and visualization of dynamic spill features with the sensitivity of environmental elements and value of human uses, the benefits of potential response actions can be compared, helping to develop an appropriate response strategy. The oil spill process simulation enables the response authorities to judge better the complexity and dynamic behavior of the systems and processes behind the potential environmental impact assessment and thereby better control the oil combat action.

Roughness and storage capacity of freshwater ice in the Straits of Mackinac

In the event of a maritime oil spill in winter conditions, the fate of oil released under ice presents considerable difficulties with respect to detection, containment and recovery compared to spills that form slicks in open water. This study presents the first quantification of roughness and associated storage capacity of the ice-water interface for freshwater ice in the Laurentian Great Lakes in North America. Ground Penetrating Radar (GPR) observations are used to retrieve ice thicknesses every 2.5 cm on a grid over ice ranging between 0.26 and 0.48 m in the Straits of Mackinac to derive a digital elevation model of the ice bottom. The root mean square of height deviations of the ice underside is observed to be 0.03 m (over a correlation length of approximately 20 m) with a storage capacity of 0.03 m3/m2. The observed physical characteristics relevant to oil entrainment at the ice underside are similar to those reported for first year sea ice and may store similar quantities of oil during the initial spill. However, the difference in the physical structure between first year ice (with brine channels) and freshwater ice (consolidated ice cap) may result in a disparity in the timing of oil appearance, and require considerably different remediation treatment.