Research Papers: Ocean Engineering

Analyses of Extreme Wave Heights in the Gulf of Mexico for Offshore Engineering Applications

[+] Author and Article Information
Vijay Panchang

Texas A&M University,
Maritime Systems Engineering Department,
200 Seawolf Parkway,
Galveston, TX 77553
e-mail: panchanv@tamug.edu

Chan Kwon Jeong

Dockwise USA,
16340 Park Ten Place,
Suite 200,
Houston, TX 77084
e-mail: chankwon.jeong@gmail.com

Zeki Demirbilek

U.S. Army Engineer Research
and Development Center,
Coastal & Hydraulics Laboratory,
3909 Halls Ferry Road,
Vicksburg, MS 39180
e-mail: zeki.demirbilek@usace.army.mil

1Corresponding author.

Contributed by the Ocean, Offshore, and Arctic Engineering Division of ASME for publication in the JOURNAL OF OFFSHORE MECHANICS AND ARCTIC ENGINEERING. Manuscript received May 14, 2012; final manuscript received September 9, 2012; published online May 2, 2013. Assoc. Editor: Hideyuki Suzuki.

J. Offshore Mech. Arct. Eng 135(3), 031104 (May 02, 2013) (15 pages) Paper No: OMAE-12-1048; doi: 10.1115/1.4023205 History: Received May 14, 2012; Revised September 09, 2012

The 2004–2008 hurricane season in the Gulf of Mexico (GOM) saw several exceedances of what was regarded, prior to that period, as the 100-year significant wave heights (SWHs) that are used for the design of offshore oil and gas facilities. As a result, these facilities sustained considerable damage and disrupted U.S. energy supplies. The wave climatology in the GOM is therefore studied in detail. A 51-year database of SWHs was constructed by using a combination of wind and wave models, and both individual wave heights and statistical measures were validated, to the extent possible, using buoy data. Analyses of the modeled data show that there is an increasing trend in the annual maximum SWHs in the eastern part of the GOM; the maximum trend is approximately 5.6 cm/year, which is of the same magnitude as that reported for the U.S. west coast. The western part; on the other hand, shows a decreasing trend. The maximum estimated 100-year SWHs (denoted by SWH100) are 19.1 m, 22.6 m and 26.7 m for the Gumbel, Weibull, and the GEV distributions, respectively. The estimates obtained here using the Weibull distribution are comparable to those obtained independently by API (API—American Petroleum Institute, 2007, “Interim Guidance on Hurricane Conditions in the Gulf of Mexico,” API Bulletin No. 2INT-MET). However, the use of objective criteria to identify the optimal distribution suggests that the GEV estimates are to be preferred if the engineer wishes to emphasize the upper tail where extremes are likely to occur. The maximum increase in the SWH100 due to the 2004–2008 season is of the order of 0.9 m to 2.7 m (depending as the distribution). Information generated here is intended to supplement the design recommendations provided by API (American Petroleum Institute, 2007, “Interim Guidance on Hurricane Conditions in the Gulf of Mexico,” API Bulletin No. 2INT-MET).

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Fig. 1

Gulf of Mexico, map and bathymetry (m)

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Fig. 2

Approximate locations of NDBC buoys in the Gulf of Mexico

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Fig. 3

Wind speeds and SWH's during Hurricane Ike (at 1200 UTC 9 Sept. 2008): (a) RV-model wind, (b) H*Wind, (c) modified RV-model wind, (d) SWH (m) using RV-model wind, (e) SWH (m) using modified RV-model wind, (f) the difference SWH (m) between (d) and (e)

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Fig. 4

Integration of windfields

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Fig. 5

SWH contour (a) and SWH comparison at buoy 42,001(b)

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Fig. 6

Modeled SWHs for Hurricane Ivan

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Fig. 8

SWH comparison during Hurricane Camille (Aug. 1969)

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Fig. 9

Comparison of monthly maxima for the eleven NDBC buoys

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Fig. 10

Best-fit lines for two groups of monthly maxima

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Fig. 11

Number of times SWH > 10 m: 1958−2003 (a), and 1958–2008 (b)

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Fig. 12

Trend distribution

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Fig. 13

Modeled and buoy annual maxima

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Fig. 14

Estimated SWH100 using the Gumbel method and 46 years (a) and 51 years (b) of data

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Fig. 15

Estimated SWH100 using the Weibull method and 46 years (a) and 51 years (b) of data

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Fig. 16

Estimated SWH100 using the GEV method and 46 years (a) and 51years (b) of data

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Fig. 17

Variation of optimal distribution with h (GEV: red, Gumbel: blue)

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Fig. 18

SWHs corresponding to different return periods




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