Extrapolation of Historical Storm Data for Estimating Design-Wave Heights
- C. Petrauskas (Chevron Oil Field Research Co.) | P.M. Aagaard (Chevron Oil Field Research Co.)
- Document ID
- Society of Petroleum Engineers
- Society of Petroleum Engineers Journal
- Publication Date
- March 1971
- Document Type
- Journal Paper
- 23 - 37
- 1971. Society of Petroleum Engineers
- 5.2.1 Phase Behavior and PVT Measurements, 4.5.2 Platform Design, 4.3.4 Scale
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An improved method is presented for selecting offshore structure design waves by extrapolating historical storm data to obtain extreme value statistics. The method permits flexibility in choice of distribution functions through use of computerized procedures, estimates extrapolated wave-height procedures, estimates extrapolated wave-height uncertainty due to small sample size, and includes criteria for judging whether or not given wave-height values can be represented by one or more of the distributions implemented in the method. The relevance of uncertainty to selection of design-wave heights is discussed and illustrated.
The problem of selecting design-wave heights for offshore platforms has many facets, ranging from the development of oceanographic data to the selection of the prudent level of engineering risk for a particular installation. This paper deals only with part of the problem; it describes an improved method for using the small available amount of wave-height information to estimate the extreme value statistics and associated uncertainties for the large storm waves that have a very low probability of occurrence. probability of occurrence. Hindcast wave-height information for design-wave studies usually covers a period of historical record that is shorter than the return period selected for acceptable engineering risk. Return periods commonly used for selection design waves are 100 years or more, but good meteorological data, on Which the calculated wave heights are based, can rarely be obtained for periods covering more than 50 to 60 years. As a consequence, extrapolations to longer return periods are necessary.
Present methods for making the extrapolation employ probablistic models through the use of special probability graph papers on which a family of distribution functions plot as straight lines. The wave heights are plotted vs their "plotting-position" return period, and a straight line fitted to the plotted data is extended beyond the data to estimate extreme wave heights for return periods of interest. The methods are described in periods of interest. The methods are described in numerous technical papers and books; Refs. 1 through 5 are examples.
The shortcomings of the present commonly used methods are: (1) the straight line drawn through the data is in most cases visually fit to the data, thus is subject to error; and (2) no information is available on the uncertainty of the resulting extrapolation. These shortcomings have been discussed by many authors and many of their concepts influenced this study.
The improved method presented in this paper offers: (1) greater flexibility in the choice of distributions through computerized procedures, (2) guidelines for picking the "best" distribution from several implemented in the method, and (3) procedures for estimating the uncertainty of procedures for estimating the uncertainty of extrapolated wave heights.
Procedures described in this paper for extrapolating hindcast storm-wave heights and estimating uncertainty intervals to the extrapolated values are recommended as aids in selecting the design-wave height. The results of the extrapolating procedure and related uncertainty considerations procedure and related uncertainty considerations are only aids to help the engineer assess the risks associated with his design. The actual selection of the design-wave height is a matter of engineering judgment. The choice is subjective and will vary according to the risk chosen for the design.
Further consideration of ways to decrease the span of be uncertainty intervals is warranted. Increasing the number of years represented in the sample along with the number of storms is a direct way to decrease the span. In the areas of the world having poor weather records the sample size will be marginal for many years to come.
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