Spill Sizes Research Articles

UNDERGROUND CRUDE OIL PIPELINE LEAKAGE DETECTION USING DEXINED DEEP LEARNING TECHNIQUES AND LAB COLOR SPACE

Computer vision plays a big role in pipeline leakage detection systems and is one of the latest techniques. Still, it requires a powerful image-processing algorithm to detect objects. The purpose of this work is to develop and implement spill detection in oil pipes caused by leakage using images taken by a drone equipped with a Raspberry Pi 4. The acquired images are sent to the base station along with the global positioning system (GPS) location of the captured images via the message queuing telemetry transport Internet of Things (MQTT IoT) protocol. At the base station, images are processed to identify contours by dense extreme inception networks for edge detection(DexiNed) deep learning techniques based on holistically-nested edge detection(HED) and extreme inception (Xception) networks. This algorithm is capable of finding many contours in images. To find a contour with black color, the CIELAB color space (LAB) has been used. The proposed algorithm removes small contours and computes the area of the remaining contours. If the contour is above the threshold value, it is considered a spill; otherwise, it will be saved in a database for further inspection. For testing purposes, three different spill areas were implemented with spill sizes of (1 m^2,2 m^2 ,and 3 m^2). Images have been captured at three different heights (5 m, 10 m, and 15 m) by the drone used to capture the images. The result shows that effective detection has been obtained at 10 meters high. To monitor the entire system, a web application has been integrated into the base station.

Assessing spill fire characteristics through machine learning analysis

A fuel spill can be a source of risk-significant fire scenarios in nuclear power plants (NPPs). Fuels can leak from main components, such as pumps, turbine lubrification lines, hydraulic valves, and diesel generators. Once ignited, a spill fire has a complex, dynamic changing burning area due to the fuel spread and burning. To quantify spill-fire consequences in NPPs, it is essential to analyze the spread of the liquid fuel and the fuel-burning behavior. In the current study, past spill fire experimental data are collected to analyze the spreading and burning behaviors for different spill sizes and fuels. Random forest machine learning (ML) models are used to evaluate the most important parameters that impact the fire scenario conditions and provide a computationally efficient model to support fire probabilistic risk assessment. The results show the importance of the fuel leakage rate or quantity, the spill surface slope, substrate material, and fuel properties.

Responses of Wild Finescale Dace (Phoxinus neogaeus) to Experimental Spills of Cold Lake Blend Diluted Bitumen at the International Institute for Sustainable Development-Experimental Lakes Area, Northwestern Ontario.

Pipelines carrying diluted bitumen (dilbit) traverse North America and may result in dilbit release into sensitive freshwater ecosystems. To better understand the potential effects of a freshwater oil release, the Boreal-lake Oil Release Experiment by Additions to Limnocorrals project at the International Institute for Sustainable Development-Experimental Lakes Area (Ontario, Canada) modeled seven dilbit spills contained within a 10-m diameter of littoral limnocorrals in a boreal lake. Wild finescale dace (Phoxinus neogaeus) were released in the limnocorrals 21 days after oil addition and remained there for 70 days. Dilbit volumes covered a large range representing a regression of real spill sizes and total polycyclic aromatic compounds (TPAC) between 167 ng L-1 day-1 and 1989 ng L-1 day-1 . We report the effects of chronic exposure on reproductive potential as well as physiological responses in the gallbladder and liver. In exposures >1000 ng L-1 day-1 , there was a significant decrease in fish retrieval, culminating in zero recapture from the three highest treatments. Among the fish from the limnocorrals with lower levels of TPAC (<500 ng L-1 day-1 ), effects were inconsistent. Gallbladder bile fluorescence for a naphthalene metabolite was significantly different in fish from the oil-exposed limnocorrals when compared to the lake and reference corral, indicating that fish in these lower exposures were interacting with dilbit-derived polycyclic aromatic compounds. There were no significant differences in condition factor, somatic indices, or hepatocyte volume indices. There were also no significant changes in the development of testes or ovaries of exposed dace. The results from the present study may serve to orient policymakers and emergency responders to the range of TPAC exposures that may not significantly affect wild fish. Environ Toxicol Chem 2022;41:2745-2757. © 2022 SETAC.

An optimized metamodel for predicting damage and oil outflow in tanker collision accidents

Society is concerned about maritime accidents since pollution, such as oil spills from ship accidents, adversely affects the marine environment. Operational and strategic pollution preparedness and response risk management are essential activities to mitigate such adverse impacts. Quantitative risk models and decision support systems (DSS) have been proposed to support these risk management activities. However, there currently is a lack of computationally fast and accurate models to estimate oil spill consequences. While resource-intensive simulation models are available to make accurate predictions, these are slow and cannot easily be integrated into quantitative risk models or DSS. Hence, there is a need to develop solutions to accelerate the computational process. A fast and accurate metamodel is developed in this work to predict damage and oil outflow in tanker collision accidents. To achieve this, multiobjective optimization is applied to three metamodeling approaches: Deep Neural Network, Polynomial Regression, and Gradient Boosting Regression Tree. The data used in these learning algorithms are generated using state-of-the-art engineering models for accidental damage and oil outflow dynamics. The multiobjective optimization approach leads to a computationally efficient and accurate model chosen from a set of optimized models. The results demonstrate the metamodel’s robust capacity to provide accurate and computationally efficient estimates of damage extents and volume of oil outflow. This model can be used in maritime risk analysis contexts, particularly in strategic pollution preparedness and response management. The models can also be linked to operational response DSS when fast, and reasonably accurate estimates of spill sizes are critical.

Performance of suspension bridge hangers exposed to hazardous material fires considering wind effects

Traffic accidents involving vehicles transporting hazardous materials (HazMat) can cause serious fire hazards, threatening the safety of bridge infrastructure as well as nearby traffic. For critical bridges such as long-span cable-stayed and suspension bridges, fire hazards can not only cause severe structural damage, but also serious traffic disruption, congestion, and accidents. Unlike short-span bridges, long-span cable-supported bridges often experience considerable wind effects at the height of the bridge deck which can significantly influence fire hazards. As the critical components of cable-supported bridges, the failure of cables or hangers due to fire may trigger progressive failure of the bridge structure. Existing studies on fire simulation of long-span bridges, however, are very limited. Typical fire hazard scenarios from vehicles transporting hazardous material (HazMat) are simulated with fire dynamics simulation (FDS) software on a suspension bridge with a focus on the threats to hangers. To more realistically consider the potential fire hazards to bridge hangers of long-span bridges, appropriate fuel size, transverse offset distance, and wind effects are considered. The study of a baseline scenario is carried out first and followed by parametric studies to investigate the effects of wind speeds, longitudinal offsets, hazardous material types and spill sizes on the fire simulation results.

Oil spill damage: a collision scenario and financial liability estimations for the Northern Sea Route area

ABSTRACT The global demand in energy resources is moving the petroleum industry to the Arctic with its huge resource potential. The lack of infrastructure onshore increases the role of the Arctic marine shipping and the importance of the Northern Sea Route (NSR). Shipping within NSR waters is associated with challenges and risks, including environmental ones, and may lead to high losses caused by an accidental oil spill. The present paper provides a description and the results from the application of a simulation model for selected tanker collision scenarios with an evaluation of possible oil spill sizes as result of discharge time, penetration depth, energy and force applied. NSR navigation data from 2013, the year with the record number of transits through NSR, were studied. These were used to generate probable oil spill scenarios caused by tanker collision, and financial liabilities for environmental damage were calculated using existing international and Russian methods.

A Bayesian Network risk model for assessing oil spill recovery effectiveness in the ice-covered Northern Baltic Sea

The Northern Baltic Sea, as one of the few areas with busy ship traffic in ice-covered waters, is a typical sea area exposed to risk of ship accidents and oil spills in ice conditions. Therefore, oil spill capability for response and recovery in this area is required to reduce potential oil spill effects. Currently, there are no integrated, scenario-based models for oil spill response and recovery in ice conditions. This paper presents a Bayesian Network (BN) model for assessing oil spill recovery effectiveness, focusing on mechanical recovery. It aims to generate holistic understanding and insights about the oil spill-to-recovery phase, and to estimate oil recovery effectiveness in representative winter conditions. A number of test scenarios are shown and compared to get insight into the impact resulting from different oil types, spill sizes and winter conditions. The strength of evidence of the model is assessed in line with the adopted risk perspective.

Produced Water Surface Spills and the Risk for BTEX and Naphthalene Groundwater Contamination

The widespread use of unconventional drilling involving hydraulic fracturing (“fracking”) has allowed for increased oil-and-gas extraction, produced water generation, and subsequent spills of produced water in Colorado and elsewhere. Produced water contains BTEX (benzene, toluene, ethylbenzene, xylene) and naphthalene, all of which are known to induce varying levels of toxicity upon exposure. When spilled, these contaminants can migrate through the soil and contaminant groundwater. This research modeled the solute transport of BTEX and naphthalene for a range of spill sizes on contrasting soils overlying groundwater at different depths. The results showed that benzene and toluene were expected to reach human health relevant concentration in groundwater because of their high concentrations in produced water, relatively low solid/liquid partition coefficient and low EPA drinking water limits for these contaminants. Peak groundwater concentrations were higher and were reached more rapidly in coarser textured soil. Risk categories of “low,” “medium,” and “high” were established by dividing the EPA drinking water limit for each contaminant into sequential thirds and modeled scenarios were classified into such categories. A quick reference guide was created that allows the user to input specific variables about an area of interest to evaluate that site’s risk of groundwater contamination in the event of a produced water spill. A large fraction of produced water spills occur at hydraulic-fracturing well pads; thus, the results of this research suggest that the surface area selected for a hydraulic-fracturing site should exclude or require extra precaution when considering areas with shallow aquifers and coarsely textured soils.

The effects of oil spills on marine fish: Implications of spatial variation in natural mortality

The effects of oil spills on marine biological systems are of great concern, especially in regions with high biological production of harvested resources such as in the Northeastern Atlantic. The scientific studies of the impact of oil spills on fish stocks tend to ignore that spatial patterns of natural mortality may influence the magnitude of the impact over time. Here, we first illustrate how spatial variation in natural mortality may affect the population impact by considering a thought experiment. Second, we consider an empirically based example of Northeast Arctic cod to extend the concept to a realistic setting. Finally, we present a scenario-based investigation of how the degree of spatial variation in natural mortality affects the impact over a gradient of oil spill sizes. Including the effects of spatial variations in natural mortality tends to widen the impact distribution, hence increasing the probability of both high and low impact events.

Automatic Mexico Gulf Oil Spill Detection from Radarsat-2 SAR Satellite Data Using Genetic Algorithm

In this work, a genetic algorithm is exploited for automatic detection of oil spills of small and large size. The route is achieved using arrays of RADARSAT-2 SAR ScanSAR Narrow single beam data obtained in the Gulf of Mexico. The study shows that genetic algorithm has automatically segmented the dark spot patches related to small and large oil spill pixels. This conclusion is confirmed by the receiveroperating characteristic (ROC) curve and ground data which have been documented. The ROC curve indicates that the existence of oil slick footprints can be identified with the area under the curve between the ROC curve and the no-discrimination line of 90%, which is greater than that of other surrounding environmental features. The small oil spill sizes represented 30% of the discriminated oil spill pixels in ROC curve. In conclusion, the genetic algorithm can be used as a tool for the automatic detection of oil spills of either small or large size and the ScanSAR Narrow single beam mode serves as an excellent sensor for oil spill patterns detection and surveying in the Gulf of Mexico.

A framework for risk analysis of maritime transportation systems: A case study for oil spill from tankers in a ship–ship collision

This paper proposes a framework for risk analysis of maritime transportation systems, where risk analysis is understood as a tool for argumentative decision support. Uncertainty is given a more prominent role than in the current state of art in the maritime transportation application area, and various tools are presented for analyzing uncertainty. A two-stage risk description is applied. In the first stage, Bayesian Network (BN) modeling is applied for probabilistic risk quantification. The model functions as a communication and argumentation tool, serving as an aid to thinking in a qualitative evidence and assumption effect assessment. The evidence assessment is used together with a sensitivity analysis to select alternative hypotheses for the risk quantification, while the assumption effect assessment is used to convey an argumentation beyond the model. Based on this, a deliberative uncertainty judgment is made in the second risk analysis stage, which is supplemented with a global strength of evidence assessment. The framework is applied to a case study of oil spill from tanker collisions, aimed at response capacity planning and ecological risk assessment. The BN-model is a proactive and transferable tool for assessing the occurrence of various spill sizes in a sea area. While the case study uses evidence specific to the Gulf of Finland, the model and risk analysis approach can be applied to other areas. Based on evaluation criteria and tests for the risk model and risk analysis, it is found that the model is a plausible representation of tanker collision oil spill risk.

Estimation of potential impacts and natural resource damages of oil

Methods were developed to estimate the potential impacts and natural resource damages resulting from oil spills using probabilistic modeling techniques. The oil fates model uses wind data, current data, and transport and weathering algorithms to calculate mass balance of fuel components in various environmental compartments (water surface, shoreline, water column, atmosphere, sediments, etc.), oil pathway over time (trajectory), surface distribution, shoreline oiling, and concentrations of the fuel components in water and sediments. Exposure of aquatic habitats and organisms to whole oil and toxic components is estimated in the biological model, followed by estimation of resulting acute mortality and ecological losses. Natural resource damages are based on estimated costs to restore equivalent resources and/or ecological services, using Habitat Equivalency Analysis (HEA) and Resource Equivalency Analysis (REA) methods. Oil spill modeling was performed for two spill sites in central San Francisco Bay, three spill sizes (20th, 50th, and 95th percentile volumes from tankers and larger freight vessels, based on an analysis of likely spill volumes given a spill has occurred) and four oil types (gasoline, diesel, heavy fuel oil, and crude oil). The scenarios were run in stochastic mode to determine the frequency distribution, mean and standard deviation of fates, impacts, and damages. This work is significant as it demonstrates a statistically quantifiable method for estimating potential impacts and financial consequences that may be used in ecological risk assessment and cost-benefit analyses. The statistically-defined spill volumes and consequences provide an objective measure of the magnitude, range and variability of impacts to wildlife, aquatic organisms and shorelines for potential spills of four oil/fuel types, each having distinct environmental fates and effects.

Comparing Oil Spill Rates Using Different Data Sources1

ABSTRACT Different sources of data on past oil spill incidents contain different kinds of information about each incident and different degrees of accuracy. The appropriate data can be used to develop spill statistics and spill rate relationships. This paper examines data on reported oil spills that have occurred in the United States. Characteristics studied include the number of spills, spill sizes, spill sources, and the types of oil spilled. Studying characteristics of past spills can help government and industry to determine the scope of oil spill prevention policies and response planning methods. The main data sources used for this paper include the Oil Spill Intelligence Report's International Oil Spill Statistics annual summaries and the National Response Center online database. This report provides a discussion of the accuracy of information from sources of oil spill data, to help support the development of spill statistics and spill rate relationships.

Financial Implications of Hypothetical San Francisco Bay Oil Spill Scenarios: Response, Socioeconomic, and Natural Resource Damage Costs

ABSTRACT This study provides a comprehensive examination of the use of trajectory modeling to estimate financial impacts of oil spills, including natural resource damages, response costs, and socioeconomic costs, as well as an opportunity to examine how spill size, oil type, response strategy, and probabilistic trajectory factors impact costs. The inclusion of NRDA, response, and socioeconomic costs in the modeling allows for an assessment of the relative proportion of NRDA costs to response and socioeconomic costs to further support the findings of past studies that refute the myth that NRDA costs are the overriding factors in most spill cases. The study demonstrates the overall financial and NRDA benefits of dispersant use. Estimated total bio-economic costs for oil spill scenarios involving four oil types and three spill sizes for two locations in San Francisco Bay, were modeled. Assuming present-day mechanical-only response, total costs range from $30 to $520 million. Estimated total bioeconomic costs would be reduced to $11 to $113 million if dispersants were used with high effectiveness. Dispersant use would reduce response costs, and if used effectively, could reduce NRDA and socioeconomic damages substantially, as both of these costs are driven by the amount of surface and shoreline oiling.

Analysis of US Oil Spill Trends to Develop Scenarios for Contingency Planning

ABSTRACT A method for using past US oil spill data to project potential future vessel spill sizes was demonstrated including methods for taking into account vessel type and local factors (e.g., vessel traffic, navigational hazards, and regulations) and implementation of spill prevention measures (e.g., tanker double-hulls). A methodology for determining “theoretical” (OPA 90-defined) vs. “most-likely” worst-case oil discharge scenarios was also demonstrated. Past vessel spills were analyzed for vessel-and spill cause-specific percent cargo or fuel outflow. Distributions of outflow percentages were then imposed on various annual vessel traffic patterns to determine the probability distribution functions of spill types that would be expected if there were spills.

Evaluation of Select Trade-Offs between Ground-Water Remediation and Waste Minimization for Petroleum Refining Industry

An investigation comparing environmental remediation alternatives and attendant costs for a hypothetical refinery site located in the Arkansas River alluvium was completed. Transport from the land's surface to and through the ground water of three spill sizes was simulated, representing a base case and two possible levels of waste minimization. Remediation costs were calculated for five alternative remediation options, for three possible regulatory levels and alternative site locations, for four levels of technology improvement, and for eight different years. The work focused on the refinery manager charged with complying with environmental regulations within an economically sound framework. These individuals are typically confronted with the mandate of meeting environmental regulation without access to necessary information. It is appropriate from environmental and economic perspectives to initiate significant efforts and expenditures that are necessary to minimize the amount and type of waste produced and disposed during refinery operations; or conversely, given expected improvements in technology, is it better to wait until remediation technologies improve, allowing greater environmental compliance at lower costs? These types of decisions are made more difficult given the uncertainties associated with future regulatory levels necessary to ensure compliance. The present work used deterministic models to track a light nonaqueous phase liquid (LNAPL) spill through the unsaturated zone to the top of the water table. Benzene leaching from LNAPL to the ground water was further routed through the alluvial aquifer. Contaminant plumes were simulated over 50 yr of transport and remediation costs assigned for each of the five treatment options for each of these years. The results of these efforts show that active remediation is most cost effective after a set point or geochemical quasi-equilibrium is reached, where long-term improvements in technology greatly tilt the recommended option toward remediation. Finally, the impacts associated with increasingly rigorous regulatory levels present potentially significant penalties for the remediation option, but their likelihood of occurrence is difficult to define.

Modelling Navigational Risk and Oil Spill Probabilities

This paper examines first a statistical modelling of the number of navigational accidents (collisons, groundings and strikings) involving tankers and freighters in Canadian waters; it then looks at a direct method of modelling oil spill frequency and magnitude, given a navigational accident. The former is used to examine various hypotheses in the literature regarding the impact of various factors on navigational risk. The latter is based on a direct probability tree analysis which allows the estimation of detailed oil spill impacts by facilitating the examination of representative spill sizes.

Contingency Planning: Implementation Is The Key

ABSTRACT The two basic components of oil spill contingency planning are developing the plan and implementing the plan. An organization with an effective oil spill contingency plan will have considered both components. Armed with thick oil spill contingency plans, companies expect to be able to respond adequately to major oil spills. For several reasons, this expectation may be unrealistic. For example, the plans may incorporate inadequate appraisals of available response assets, they may have been developed merely to satisfy regulatory requirements, or they may fail to consider various spill scenarios. Plans based on unattainable or unrealistic expectations end up on the shelf collecting dust. Thus, one of the first things to consider in contingency planning is what the plan will be expected to do. Another factor in the effectiveness of a contingency plan is its format. Oil spill contingency plans that are comprehensive and easy to use are essential. It is useful to divide the plan into three major sections: response procedures, background information, and scenario development. The response procedures section should be relatively short and contain step-by-step procedures to be followed during a spill response. The background information section should contain the background information accumulated during the planning period. The scenario development section should contain the scenarios identified for various spill sizes. An excellent contingency plan is of limited value if it is not effectively implemented. Effective implementation requires that everyone in the response and planning organization know the company's ideas, policies, and strategies regarding oil spill response, understands his or her roles and responsibilities in preparing for and carrying out a response, and is committed to carrying out the program. Implementation is often difficult because it involves changing the organization's way of doing things. When the way an organization does business does not match a new program being implemented, leadership is required to match them, either by changing the way of doing business or by changing the program. Changing a new program could be as simple as making a decision. Changing the way an organization does business is a process and is usually very difficult, especially in a large, complex organization like an oil company.

Analysis of vapor barrier experiments to evaluate their effectiveness as a means to mitigate HF cloud concentrations

Accidental release of Hydrogen Fluoride (HF) can result in initially dense, highly reactive and corrosive gas clouds. These clouds will typically contain a mixture of gases, aerosols and droplets which can be transported significant distances before lower hazard levels of HF concentration are reached. Previous related field and laboratory experiments have been analyzed to estimate the effectiveness of barrier devices. The experiments were examined to determine their relevance to Hydrogen Fluoride spill scenarios. Wind tunnel and field data were compared where possible to validate the laboratory experiments. Barrier influence on peak concentrations, cloud arrival time, peak concentration arrival time, and cloud departure time were determined. These data were used to develop entrainment models to incorporate into integral and depth averaged numerical models. The models were then run to examine barrier performance for a typical Hydrogen Fluoride spill for a wide range of vapor barrier heights, spill sizes, meteorological conditions and release configurations. Finally the results of the data analysis and numerical sensitivity study were interpreted and expressed in a form useful to evaluate the efficiency of vapor barrier mitigation devices.

Numerical prediction of NG spread following intermediate-size LNG spills from ship tankers

The paper presents a computational model for the numerical prediction of the three-dimensional, time-dependent spread of natural gas (NG) in the atmosphere, following the accidental release of liquefied NG from a ship tanker in the open sea. The model is designed to predict the consequences of liquefied NG spills of intermediate size in which the disturbance to the surrounding atmospheric airflow caused by the effect of the NG release is comparable in magnitude to the one introduced by the tanker's obstruction to the flow. It is applied to predict the NG concentrations arising from two different spill sizes, and typical results are presented and discussed. They are demonstrated to be plausible and informative.