Sea state forecasting is of primary importance for marine operations related to offshore oil&gas industry. Operative decisions are based on marine weather forecasts. For this reason, at least once a day a bulletin of marine weather forecasts is delivered on board. Bulletins give a very good general overview of weather for the next days, while sometime they are not accurate relatively to the forecasted seastate values or their time of occurrence. In this work has been developed an Artificial Intelligence model named time delayed neural networks (TDNN) to improve the accuracy of short term sea state forecasting, combining bulletins forecasts with buoy measurements. The TDNN parameters are optimized by Genetic Algorithms. It has been found that the optimized TDNN produces very good forecasts, always outperforming bulletins, at least up to 24 hours ahead. Two configurations of TDNN are analyzed: in the first one, TDNN is trained with only buoy measurements, while in the second one TDNN is trained with both buoy and bulletin data. For 24 hours lead time, the combined use of buoy measurements and bulletins as input has been demonstrated to give better results than the use of only buoy measurements.

The transition to a decarbonised energy system requires gathering, transport and distribution over short and long distances of CO2 and H2. For such systems, concerning offshore applications, the track record is very limited or null. The scope of this paper is to provide an overview of critical safety aspects and knowledge gaps associated with CO2 and H2 offshore pipelines. This will pave the way for a novel methodology to assess technological risk and will open the path for designing the roadmap to develop new tools for the evaluation of the hazards and their consequences. The starting ground of the novel methodology is the review of the state of art of safety aspects for CO2 and H2 offshore pipeline systems. The paper presents the status of international regulations, applicable tools and methodologies for safety analysis in the new transport scenarios and the available data on fluid release and its consequences (asphyxiation, flammable gas clouds etc). In addition, a specific approach to underwater dispersion modelling is proposed as well as the effort to collect experimental data for validation purpose. The review of the state of the art revealed that, particularly for the offshore system, safety issues are compounded by limited or no experience, lack of accident statistics on which to base risk assessment, limited availability of experimental data on underwater release and dispersion of the product into the atmosphere, toxicity and impact on health, safety and the environment. Last but not least, international regulations need to improve and reach a sufficient level of definition and coverage of topics has not yet been achieved for engineering to have a solid regulatory footprint. In order to ensure that subsea pipeline systems meet the safety and environmental requirements of companies, regulations and international standards, this paper proposes a novel methodology to develop a risk assessment process, from the initial phase during design to the operational life of offshore pipeline systems, exploiting and adapting Saipem knowledge of hydrocarbon risk analysis and consequence modelling tools available to date.

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