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International audience ; The maritime supply chain of energy concerns all trips done between ports on the maritime space. The use of this space has increase since 1970. This increase is due to the globalization, a strong increase of the demand of energy and freight, containerization of goods and economies of scale. Due to the development of maritime transport, a territorialization process appears on maritime space. For Di Meo (2001) "Territorialize space is for a society to multiply places to install networks in both concrete and symbolic". These locations exist on the maritime space, and can be physical socio-economical (E.g use for navigation, exploitation) or political/legal. All these locations formalize a spatial heterogeneity and a spatial dynamic, due to the permanent evolution of maritime locations. These maritime territories can be risky for maritime transport, taking into account the environment, human activities or deliberate actions. Risks can product disruptions and affect the capacity of a spatial mediator (maritime space) to link the different parts within this mediator. The main goal of this research is to propose a modeling approach of the maritime network; we use an agent-based system to simulate vessel trajectories. This approach will be able to measure, by the spatio-temporal features of disruption, the vulnerability of the maritime network and especially the maritime supply chain of energy.

International audience ; The maritime supply chain of energy concerns all trips done between ports on the maritime space. The use of this space has increase since 1970. This increase is due to the globalization, a strong increase of the demand of energy and freight, containerization of goods and economies of scale. Due to the development of maritime transport, a territorialization process appears on maritime space. For Di Meo (2001) "Territorialize space is for a society to multiply places to install networks in both concrete and symbolic". These locations exist on the maritime space, and can be physical socio-economical (E.g use for navigation, exploitation) or political/legal. All these locations formalize a spatial heterogeneity and a spatial dynamic, due to the permanent evolution of maritime locations. These maritime territories can be risky for maritime transport, taking into account the environment, human activities or deliberate actions. Risks can product disruptions and affect the capacity of a spatial mediator (maritime space) to link the different parts within this mediator. The main goal of this research is to propose a modeling approach of the maritime network; we use an agent-based system to simulate vessel trajectories. This approach will be able to measure, by the spatio-temporal features of disruption, the vulnerability of the maritime network and especially the maritime supply chain of energy.

International audience ; The maritime supply chain of energy concerns all trips done between ports on the maritime space. The use of this space has in-crease since 1970. This increase is due to the globalization, a strong increase of the demand of energy and freight, containerization of goods and economies of scale (Rodrigue, 2013). Due to the development of maritime transport, a territorialization process appears on mari-time space (Parrain, 2012). For Di Meo (2001) "Territorialize space is for a socie-ty to multiply places to install networks in both concrete and symbolic". These lo-cations exist on the maritime space, and can be physical (e.g. weather, reefs) socio-economical (E.g use for navigation, exploitation) or political/legal (e.g. TSS, EEZ). All these locations formalize a spatial heterogeneity and a spatial dynamic, due to the permanent evolution of maritime locations. These maritime territories can be risky for maritime transport, taking into account the environment, human activities or deliberate actions. Risks can product disruptions and affect the capaci-ty of a spatial mediator (maritime space) to link the different parts within this me-diator (Gleyze, 2005). The main goal of this research is to propose a modeling ap-proach of the maritime network; we use an agent-based system to simulate vessel trajectories. This approach will be able to measure, by the spatio-temporal features of disruption, the vulnerability of the maritime network and especially the mari-time supply chain of energy.

International audience ; The maritime supply chain of energy concerns all trips done between ports on the maritime space. The use of this space has in-crease since 1970. This increase is due to the globalization, a strong increase of the demand of energy and freight, containerization of goods and economies of scale (Rodrigue, 2013). Due to the development of maritime transport, a territorialization process appears on mari-time space (Parrain, 2012). For Di Meo (2001) "Territorialize space is for a socie-ty to multiply places to install networks in both concrete and symbolic". These lo-cations exist on the maritime space, and can be physical (e.g. weather, reefs) socio-economical (E.g use for navigation, exploitation) or political/legal (e.g. TSS, EEZ). All these locations formalize a spatial heterogeneity and a spatial dynamic, due to the permanent evolution of maritime locations. These maritime territories can be risky for maritime transport, taking into account the environment, human activities or deliberate actions. Risks can product disruptions and affect the capaci-ty of a spatial mediator (maritime space) to link the different parts within this me-diator (Gleyze, 2005). The main goal of this research is to propose a modeling ap-proach of the maritime network; we use an agent-based system to simulate vessel trajectories. This approach will be able to measure, by the spatio-temporal features of disruption, the vulnerability of the maritime network and especially the mari-time supply chain of energy.

International audience ; The upsurge in piracy and the impact of recent environmental disasters have highlighted the need to improve maritime surveillance. Governmental and private initiatives have developed monitoring systems with improved acquisition and analysis capabilities. These systems rely on one major component, namely the detection of abnormal ship behaviour. This implies a detailed formalisation of expert knowledge. However, the quantity of data, the complexity of situations, the failure to take into account their spatial characteristics and the potential for the same scenario to be interpreted in different ways have proved to be significant problems. We therefore propose a new prototype for the analysis of abnormal ship behaviour. The system is based on a spatial ontology associated with a geographical inference engine. It automatically identifies suspicious vessels and associates them with probable behaviours defined by operational staff.

International audience ; The upsurge in piracy and the impact of recent environmental disasters have highlighted the need to improve maritime surveillance. Governmental and private initiatives have developed monitoring systems with improved acquisition and analysis capabilities. These systems rely on one major component, namely the detection of abnormal ship behaviour. This implies a detailed formalisation of expert knowledge. However, the quantity of data, the complexity of situations, the failure to take into account their spatial characteristics and the potential for the same scenario to be interpreted in different ways have proved to be significant problems. We therefore propose a new prototype for the analysis of abnormal ship behaviour. The system is based on a spatial ontology associated with a geographical inference engine. It automatically identifies suspicious vessels and associates them with probable behaviours defined by operational staff.

International audience ; The Deepwater Horizon drilling accident that occurred on 20 April 2010 was a two-fold catastrophe. The initial total loss of the drilling rig was followed by one of the worst environmental disasters in recent history. The four million barrels of oil that were released into the Gulf of Mexico continue to impact human activities in the area. The Macondo well incident (Mississippi Canyon 252-1, leased by BP as the primary operator) was the first deep subsea blowout in the history of the oil and gas industry, and both the United States' government and the private sector were unprepared to deal with it. All of the safety system's lines of defense failed and the response required multiple courses of actions to be taken to address an unprecedented situation. It was imperative to deliver the best engineering solutions under intense and ongoing pressure in a very harsh and highly stressful operational environment. In this paper we review the engineering solutions considered by the response teams. The first part of the paper gives a brief presentation of our approach to the case study. The second reviews post-blowout events, the initial organizational response and the discovery of leaks. The final part presents how the statement of the problem was developed by the organization and how the response was structured. We then analyse the engineering solutions and finally, show how the organization implemented these solutions to control the source of the spill, recover the effluent and seal the well. In conclusion, we provide an overview of the engineering work that was carried out and preview our forthcoming work. We assume that the response to the Deepwater Horizon oil spill was efficient from an operational point of view. Therefore, our findings will be used to develop a new approach to the analysis of major accidents and ultimately shape the design of a new set of disaster management guidelines.

International audience ; The Deepwater Horizon drilling accident that occurred on 20 April 2010 was a two-fold catastrophe. The initial total loss of the drilling rig was followed by one of the worst environmental disasters in recent history. The four million barrels of oil that were released into the Gulf of Mexico continue to impact human activities in the area. The Macondo well incident (Mississippi Canyon 252-1, leased by BP as the primary operator) was the first deep subsea blowout in the history of the oil and gas industry, and both the United States' government and the private sector were unprepared to deal with it. All of the safety system's lines of defense failed and the response required multiple courses of actions to be taken to address an unprecedented situation. It was imperative to deliver the best engineering solutions under intense and ongoing pressure in a very harsh and highly stressful operational environment. In this paper we review the engineering solutions considered by the response teams. The first part of the paper gives a brief presentation of our approach to the case study. The second reviews post-blowout events, the initial organizational response and the discovery of leaks. The final part presents how the statement of the problem was developed by the organization and how the response was structured. We then analyse the engineering solutions and finally, show how the organization implemented these solutions to control the source of the spill, recover the effluent and seal the well. In conclusion, we provide an overview of the engineering work that was carried out and preview our forthcoming work. We assume that the response to the Deepwater Horizon oil spill was efficient from an operational point of view. Therefore, our findings will be used to develop a new approach to the analysis of major accidents and ultimately shape the design of a new set of disaster management guidelines.