LAUSR

Abstract Logistics support to offshore operations is challenging, especially under severe environmental conditions such as those in the Arctic and sub-Arctic. The dominant environmental conditions, including waves, wind, poor visibility and the presence of icebergs and sea ice determine the mode and success of logistics support. Use of helicopters as a mode of logistics transport becomes ineffective when the distance is longer, the visibility is low, or the weather is stormy. Marine logistics support is more reliable and versatile. The present work focuses on developing a model for assessing risk associated with marine logistics operations in remote offshore locations (beyond helicopter reach) frequented with harsh environmental conditions (high winds, waves, and icy conditions). The key factors that affect such operations are identified and failure models are developed using fault trees. As an improvement, advance fault trees are adopted to relax the inherent limitations of the primary model. Uncertainties in both data and model are considered using the fuzzy inference system and evidence theory. Application of the proposed model is demonstrated through a case-study concerning a remote North Atlantic offshore operation. The contribution of this study is the identification of the key factors controlling the marine logistics operation and the development of a robust risk model that helps to analyze criticality of the contributing factors. The proposed model has the potential to help to develop innovative risk management strategies to support offshore operations.