Ocean swell is often an important factor for offshore operations. A global directional spectra swell model has been developed for forecasting or hind casting swell conditions at sites anywhere in the world. The model calculates directional wave spectra due to both local winds and distant storms which may be located in either hemisphere of a given ocean. Computer files contain geographical boundary and coordinate system transformation information for the Northern and Southern Hemisphere parts of the Pacific Ocean, the Atlantic Ocean, and the Indian Ocean. For input wind fields in either hemisphere of a selected ocean at any time, coordinate transformations place an ocean-wide grid system over the appropriate hemisphere. Near and within input wind fields, waves are generated by a Miles-Phillips type growth mechanism, dissipated by opposing winds and wave breaking, and numerically propagated. Analytical techniques propagate wave energy over long distances to sites which may be located in hemispheres opposite wave generation regions. Swell propagating from generation regions is combined with locally generated wave energy to provide directional spectra. As a result of wave generation only in specified regions and analytical rather than numerical propagation over long distances, the model is efficient for offshore applications and avoids several problems associated with other available numerical wave models. The global ocean swell model has been extensively tested in simulations but only limited hind cast comparisons have been made with measured wave data.


Both locally generated waves (sea) and waves generated by distant winds (swell) are important for offshore oil operations. Ocean swell, in particular, affects exploration drilling, platform installation, offshore construction, pipeline laying, and towing. For example, evaluation of swell environments at unfamiliar sites is important for drilling rig selection to meet drilling program plans.

Visual observations of swell from ships are usually of poor quality and observers do not properly distinguish between sea and swell. In-situ measured wave data which are adequate for statistical development of swell climatologist are sparse, particularly in the Southern Hemisphere where swell from storms often propagates over very long distances. Satellite wind and wave measurements, such as those made by GEOS-3 (Geodynamics Experimental Ocean Satellite) and SEASAT, can provide some global swell information but only limited data are available. Many sources of wave information, such as extreme event studies based on wave hind casts, emphasize locally severe weather situations rather than severe swell conditions which may occur during relatively good local weather. A number of state-of-the-art numerical wave models are available for forecasting or hind casting. These models, which are generally spectral models that improve on concepts originally introduced in the Pierson-Neumann James wave prediction method,1 have been frequently reviewed.2,3,4,5 However, these models do not have capability to efficiently calculate swell generated by distant storms. These models are also costly and difficult to set-up and operate on a global basis. The three main types of state-of-the-art wave models are: discrete spectral models, parametric models, and hybrid models which are a combination of the first two types.

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