A New CBR Approach to the Oil Spill Problem

Oil spills represent one of the most destructing environmental disasters. Predicting the possibility of finding oil slicks in a certain area after an oil spill can be crucial in order to reduce the environmental risks. The system presented here forecasts the presence or not of oil slicks in a certain area of the open sea after an oil spill using Case-Based Reasoning methodology. CBR is a computational methodology designed to generate solutions to a certain problem by analysing previous solutions given to previous solved problems. The proposed system wraps other artificial intelligence techniques such as a Radial Basis Function Networks, Growing Cell Structures and Principal Components Analysis in order to develop the different phases of the CBR cycle. CBR systems have never been used before to solve oil slicks problems. The proposed system uses information obtained from various satellites such as salinity, temperature, pressure, number and area of the slicks... OSCBR system has been able to accurately predict the presence of oil slicks in the north west of the Galician coast, using historical data

Forecasting the probability of finding oil slicks using a CBR system

A new predicting system is presented in which the aim is to forecast the presence of oil slicks in a certain area of the open sea after an oil spill. Case-based reasoning is a computational methodology designed to generate solutions to a certain problem by analysing previous solutions given to previous solved problems. In this case, the system designed to predict the presence of oil slicks wraps other artificial intelligence techniques such as a radial basis function networks, growing cell structures and principal components analysis in order to develop the different phases of the Case-based reasoning cycle. The proposed system uses information such as sea salinity, sea temperature, wind, currents, pressure, number and area of the slicks, …. obtained from various satellites. The system has been trained using data obtained after the Prestige oil spill, occurred in the Atlantic waters, in the northwest of Spain. The system developed has been able to accurately predict the presence of oil slicks in the north west of the Galician coast, using historical dat

A forecasting solution to the oil spill problem based on a hybrid intelligent system

Oil spills represent one of the most destructive environmental disasters. Predicting the possibility of finding oil slicks in a certain area after an oil spill can be critical in reducing environmental risks. The system presented here uses the Case-Based Reasoning (CBR) methodology to forecast the presence or absence of oil slicks in certain open sea areas after an oil spill. CBR is a computational methodology designed to generate solutions to certain problems by analysing previous solutions given to previously solved problems. The proposed CBR system includes a novel network for data classification and retrieval. This type of network, which is constructed by using an algorithm to summarize the results of an ensemble of Self-Organizing Maps, is explained and analysed in the present study. The Weighted Voting Superposition (WeVoS) algorithm mainly aims to achieve the best topographically ordered representation of a dataset in the map. This study shows how the proposed system, called WeVoS-CBR, uses information such as salinity, temperature, pressure, number and area of the slicks, obtained from various satellites to accurately predict the presence of oil slicks in the north-west of the Galician coast, using historical data

The fate of petroleum in the marine environment

This report outlines progress toward understanding the fate of petroleum spilled in the marine environment. The report updates the 1975 National Academy of Sciences report "Petroleum in the Marine Environment" and emphasizes the fate of oil in the higher latitudes. The physical, chemical, and biodegradative processes throughout the history of an oilspill are covered in this report. An attempt is made to identify processes dominating movement and weathering at various times after the spill and, when possible, to present equations for the prediction of the effects of these processes. High-priority areas for future research are outlined

Numerical Modelling of Oil Spill Transport in Tide-Dominated Estuaries: A Case Study of Humber Estuary, UK

Oil spills in estuaries are less studied and less understood than their oceanic counterparts. To address this gap, we present a detailed analysis of estuarine oil spill transport. We develop and analyse a range of simulations for the Humber Estuary, using a coupled hydrodynamic and oil spill model. The models were driven by river discharge at the river boundaries and tidal height data at the offshore boundary. Satisfactory model performance was obtained for both model calibration and validation. Some novel findings were made: (a) there is a statistically significant (p < 0.05) difference in the influence of hydrodynamic conditions (tidal range, stage and river discharge) on oil slick transport; and (b) because of seasonal variation in river discharge, winter slicks released at high water did not exhibit any upstream displacement over repeated tidal cycles, while summer slicks travelled upstream into the estuary over repeated tidal cycles. The implications of these findings for operational oil spill response are: (i) the need to take cognisance of time of oil release within a tidal cycle; and (ii) the need to understand how the interaction of river discharge and tidal range influences oil slick dynamics, as this will aid responders in assessing the likely oil trajectories

Miniaturized data loggers and computer programming improve seabird risk and damage assessments for marine oil spills in Atlantic Canada

Obtaining useful information on marine birds that can aid in oil spill (and other hydrocarbon release) risk and damage assessments in offshore environments is challenging. Technological innovations in miniaturization have allowed archival data loggers to be deployed successfully on marine birds vulnerable to hydrocarbons on water. A number of species, including murres (both Common, Uria aalge, and Thick-billed, U. lomvia) have been tracked using geolocation devices in eastern Canada, increasing our knowledge of the seasonality and colony-specific nature of their susceptibility to oil on water in offshore hydrocarbon production areas and major shipping lanes. Archival data tags are starting to resolve questions around behaviour of vulnerable seabirds at small spatial scales relevant to oil spill impact modelling, specifically to determine the duration and frequency at which birds fly at sea. Advances in data capture methods using voice activated software have eased the burden on seabird observers who are collecting increasingly more detailed information on seabirds during ship-board and aerial transects. Computer programs that integrate seabird density and bird behaviour have been constructed, all with a goal of creating more credible seabird oil spill risk and damage assessments. In this paper, we discuss how each of these technological and computing innovations can help define critical inputs into seabird risk and damage assessments, and when combined, can provide a more realistic understanding of the impacts to seabirds from any hydrocarbon release

2017 State-of the Science of Dispersants and Dispersed Oil (DDO) in U.S. Arctic Waters: Physical Transport and Chemical Behavior

Chemical dispersants were employed on an unprecedented scale during the Deepwater Horizon oil spill in the Gulf of Mexico, and could be a response option should a large spill occur in Arctic waters. The use of dispersants in response to that spill raised concerns regarding the need for chemical dispersants, the fate of the oil and dispersants, and their potential impacts on human health and the environment. Concerns remain that would be more evident in the Arctic, where the remoteness and harsh environmental conditions would make a response to any oil spill very difficult. An outcome of a 2013 Arctic oil spill exercise for senior federal agency leadership identified the need for an evaluation of the state-of-the-science of dispersants and dispersed oil (DDO), and a clear delineation of the associated uncertainties that remain, particularly as they apply to Arctic waters. The National Oceanic and Atmospheric Administration (NOAA), in partnership with the Coastal Response Research Center (CRRC), and in consultation with the U.S. Environmental Protection Agency (EPA) embarked on a project to seek expert review and evaluation of the state-of-the-science and the uncertainties involving DDO. The project focused on five areas and how they might be affected by Arctic conditions: dispersant effectiveness, distribution and fate, transport and chemical behavior, environmental impacts, and public health and safety. This publication (1 of 5) addresses efficacy and effectiveness

Oil Spill Containment and Removal in Arctic Ecosystems

Statistics on 16 arctic and subarctic oil spills, their locations, the amount of oil spilled, combatant schemes used, and causes for the spills were culled from the literature. This information has been used to analyze the effectiveness of available chemical, mechanical, and destructive means of oil recovery or disposal under arctic and subarctic conditions. The choice of the best cleanup procedures to follow in any particular instance is clouded by a number of variables and must be weighed against such considerations as wind, sea, and ice conditions, properties of the oil, and effects of chemicals on marine and wildlife. Access to remote arctic sites may well create a major difficulty. Some recommendations for further research on these problems are also given