During the last decade, increasing attention has been focused on environmental protection. For instance, the ecological effects of hydrocarbon releases in the sea are of paramount concern. One way to assess their environmental impact is to consider the amount of pollutant discharged. Effective early detection would help in revealing spills in advance and take the necessary mitigating measures to contain the released volume. Standards and guidelines are established for developing effective sensor networks in the subsea templates for monitoring purposes and data collection. Sensors provide a heterogeneous amount of information about the template they are monitoring. According to recent studies on risk assessment, the level of knowledge about a specific system is an intrinsic feature that should be considered during the assessment and evaluation phases for better managing potential increments of the risk level. The information provided by sensor networks may be used in this perspective. Sensors may be functionally placed in fault tree analyses and update the information about frequency deviation. The work in this paper is focused on risk management using such information from subsea sensor networks. A real reference case from the oil and gas industry located in an environmentally sensitive area on the Norwegian Continental Shelf is provided for testing the suggested approach. The case study refers to subsea monitoring of oil leakages from the wellhead templates. Insights from the case study highlight how sensor data analysis may improve risk management and support operational decision making.
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