Events such as the Deepwater Horizon oil spill highlight the need for improved containment response systems in response to deepwater incidents. This paper outlines numerical analysis and bridge simulation work to determine the feasibility and weather operating limits for loading and offloading operations in the US Gulf of Mexico as part of an emergency response to a potential loss of well control requiring well flow back. This work was carried out by MARIN for HWCG, a consortium of sixteen deepwater operators committed to building a safe, comprehensive and rapid response system through industry collaboration and mutual aid. The response system studied includes four key surface vessels: a mobile offshore drilling unit (MODU), a production vessel, a storage vessel and an offloading vessel. This paper focuses on the storage and offloading vessels, which are held in place by tugs with dynamic positioning (DP), as these vessels are critical to the uptime of the response system. The numerical analysis consists of simulated hawser loads and holding tug tow line loads for two sizes of storage and offloading tankers and a range of wind, current, and wave conditions. The hydrodynamic models of storage tanker, offloading tanker, and holding tugs were then input into a bridge simulator to allow real time simulation under various conditions. An experienced tanker offloading mooring master, a DP process vessel Offshore Installation Manager (OIM), and positioning tug masters used the bridge simulator to confirm feasibility and develop procedures for position keeping of the storage tanker using tugs. Weather operating windows, hawser design and tug characteristics predicted by the numerical analyses were modified as a result of the bridge simulation work. The bridge simulator is now available for training tanker, process vessel, storage tanker, and offloading tanker personnel in advance of an actual emergency response event. This paper shows how integrating numerical analysis, a bridge simulator, and actual operator input can help to solve complex operational design challenges.

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