Wave data for shallow and deep water sedimentary basins of Malaysia

Transcription

1 Advanced Science Letters Wave data for shallow and deep water sedimentary basins of Malaysia Mohammed Jameel, A.B.M. Saiful Islam, Firas A. Salman, M. Khaleel and M. Z. Jumaat Department of civil Engineering, University of Malaya, Kuala Lumpur, Malaysia Date of Submission: 30 September Date of Acceptance: 21 October Corresponding author: A.B.M. Saiful Islam Mailing Address: PhD Student, Department of civil Engineering, University of Malaya, Kuala Lumpur, Malaysia Telephones: (office), (Mobile) Fax: Corresponding author, University of Malaya, Tel:

2 Abstract: The recent years have seen significant development of offshore structures in Malaysian region for oil and gas exploration. Analyzing and studying the behavior of offshore marine structures subjected to environment conditions native to Malaysian seas offshore of Terengganu and Sarawak requires that the sea wave characteristics be properly probed. In addition, the knowledge of wave characteristics is essential for planning, design and construction of new ports coastal protection constructions, harbors and navigational channels. It correspondingly contributes to fisheries activities, navigation, marine habitat management and coastal development and planning. As this kind of research is still young for the case of Malaysian oil and gas exploration cum production activity, research methods are introduced and implemented in the study to catch on the wave characteristics in deep water be existent at offshore Terengganu and Sarawak. These essentially include obtaining reliable sea wave data for the purpose of offshore engineering design, studying the wave height distributions to predict the probability of occurrences of different sea states. Subsequently, the wave data s for the water depths of the Terengganu and Sarawak basin, which is 200m (shallow) and 2000m (ultra-deep) respectively are developed. The sea wave data have been predicted for 100 years occurrence probabilities and 1000 years return periods. Keywords: Wave data; Offshore structures; Malaysian sea; Sarawak basin; Terengganu basin; shallow and deep water. 1. INTRODUCTION For the past decades, oil and gas industry has moved towards ocean deposits due to depletion of these energy

3 resources in onshore region. The sea environmental loading acting on the oil and gas exploration structures is of great concern 1,2. Precise prediction of wave data is very essential to understand the structural response behaviors and design of offshore structures 3-5. Malaysia is having seven sedimentary basins in deep waters. Among them Terengganu and Sarawak basins are deposited with a huge amount of natural resources. The water depths of Terengganu and Sarawak basin are 200m (shallow) and 2000m (ultra-deep) respectively 6. This variation of sea environment brings a fact of interest to explore the wave behaviors. Several approaches to obtain sea wave parameters have been addressed by various researchers. Yaakob et al. 7 worked on developing a reliable and comprehensive wave database for Malaysian seas using satellite altimetry. Prior to this, the need for wave data for engineering design purposes were fulfilled by the Marine Meteorology and Oceanography, Malaysian Meteorological Service (MMS) and sometimes from Global Wave Statistics (GWS) data by the British Maritime Technology. Saleh et al. 8 identified and compared the wave characteristics in Sabah waters at five different key locations so as to determine the effects of the Northeast Monsoon (NEM) and the Southwest Monsoon (SWM) along the east and west coasts of Sabah. They collected monthly wave height and wave period data for 8 years. The significance of wave characteristics during the NEM and the SWM for the east coast (Sandakan and Tawau) and west coast (Labuan and Kota Kinabalu) of Sabah are presented in this study. The range of wave heights in coastal waters surrounding Sabah was found to be m. Wave height is usually higher than 1 m in the west coast during NEM while the east coast has a wave height of around 0.5 m for both monsoons. Marghany and Hashim 9 studied on solving the Doppler spectra equation by involving two -dimensional Fourier transform (2DFFT) to obtain a linear formula of sea radial component. The problem of influence of bandwidth on imaging moving ocean surface is analytically solved. Based on the maximum peak of Doppler spectra, the horizontal surface current is computed. The study concludes that Doppler spectra model is an appropriate method to compute the sea surface current in the RADARSAT-1 SAR

4 data for the study location at the seas offshore of Terengganu, Malaysia. Furthermore Biswas and Kara 10 introduced conservation laws of regularized long wave equation. For developing ocean wave characteristics, frequency distribution is an outstanding tool. Frequency distribution studies and return period estimations of sea waves have been covered by few investigators Caires and Sterl 14 presented global estimates of 100-year return period of significant wave heights, based on the ERA-40 reanalysis data. Their calculation of return values is based on the peaks-over-threshold method, with a threshold on the 93% level of all 6-hourly data. The large amount of data provided evidence that the distribution of significant wave height belongs to the domain of attraction of the exponential. Onni Suhaiza et al. 15 studied the suitability of determining magnitude and frequency of floods for Sarawak using Gumbel distribution based on a limited period of data. Nineteen stations were selected for the study based on the criteria stated in Hydrological Procedure No. 4 (HP4). The probability plot and flood-frequency curves by Gumbel distribution of each individual station were prepared using three different plotting position formulas (viz. Weibull, Gringorten and L-Moments). In probability distribution, the estimated values compactly summarize the characteristics of the distribution. The procedure is thus much more objective than geographical methods using eye-fitted curves. Muzathik et al. 16 presented wave measurement and wave climate prediction within Peninsular Malaysia by in-situ measurements from 1998 to The study area was contained within latitudes of 3.5 N N and longitudes E E, which is within km off the East Coast of Peninsular Malaysia. Rayleigh and Weibull density functions were used to predict wave heights. More than 60% of the annual wave energy was caused by wave heights between m. Waves with peak periods between 2 and 8 s accounted for more than 70% of the total wave energy. The extreme significant wave heights ranging 2.6 to 3.4 m obtained from Gumbel Distribution showed a marked increase compared to the values calculated using Weibull or Generalized Pareto Distributions (GPD).

5 From the existing literatures it is clear that there is lacking of sea wave characteristics of Malaysian offshore region. In addition, the probability of severe occurrences which can mostly be obtained in frequency distribution approach is also imperative for severe sea environments. Therefore, the main objective of the present study is to generate reliable wave data for Malaysian shallow and deep waters regions and to process the raw wave data into suitable frequency and probability distribution models for predicting wave occurrences in Malaysian waters. 2. MATERIALS AND METHODOLOGY It is worth mentioning that wave height data needs precise consideration of the possible sea conditions that could be encountered for any offshore structures during its intended operating lifespan From the existing literature it is found that readily available wave data for Malaysia is scarce and of questionable reliability. Presently there are only 2 such data sources and both of which are obtained from observations from volunteer ships. This situation resulted in the wave data being confined to when and where these ship set sail, consequently there are certain periods of time and at certain locations that there are no data at all. Offshore Terengganu (Longitude E, Latitude 6-8 N) and Offshore Sarawak (Longitude 111 E, Latitude 6 N) has been considered to obtain the wave data of shallow and deep water regions respectively. The investigation was based on the datasets from Yaakob et al. 20 and WorldWaves 21 respectively. Fig. 1. Mean seasonal significant wave heights over South China Sea, Peninsular Malaysia and Borneo 21. The instruments were checked and calibrated to ensure the quality of data collected. To give a better perspective on the representative wave conditions in the offshore region Malaysia, data based on in situ

6 measurements have been generated. However, recent researches have shown that satellite altimetry data may be interpreted and calibrated to provide reliable and accurate sea wave parameters for any location in the world. The following wave data was obtained from two independent sources that have based their findings on satellite altimetry: 1 year WorldWaves 21 data on a 0.5 x 0.5 grid offshore of the state of Sarawak, from the European Centre for Medium-Range Weather Forecasts (ECMWF) WAM model archive. (calibrated and corrected by Fugro OCEANOR, 2010). Research by Yaakob et al. 20 on a 2 x 2 grid for a location offshore of the East Coast of Peninsular Malaysia for 2 years. Based on the locations of known oil and gas reserves as well as possible future exploration and production activities, the location for the satellite wave data was chosen for offshore Terengganu, longitude 107 E, latitude 7 N and offshore Sarawak, longitude 111 E, latitude 6 N. Fig. 2. Location of the Malaysian oil and gas blocks, with measured wave data locations 22. The locations of targeted data 23 are illustrated in Figures 1~3, for comparison with the locations of significant wave height distributions, Malaysian oil and gas blocks and also sea depth ranges. Fig. 3. South East Asian waters including contours for water depth 21 Tables 1~2 show the corresponding summary of wave data obtained. It is to be noted that wherever the sea is idealized as regular, significant wave height and zero crossing periods are taken as wave heights and wave periods of sine waves. The altimetry data from Table 1 was extracted based on repeat cycle of the T/P satellite

7 within this area from the year 1997 to 2000, whereas the wave data from Table 2 was for the year Table 1. Four-year wave data for offshore Terengganu, 6-8 N, E 20. Corresponding to a known significant wave height H s, zero crossing period T z and the mean wind velocity u may be obtained assuming the same probability of occurrence 24. H s & T z are taken in a correlated fashion as per the empirical relation equations (1) and (2). T z 32 H s (1) g gh u s (2) Table 2. One -year wave data for offshore Sarawak, 6 N, 111 E 21. Nine numbers of sea states has been considered namely S1~S9. The matching Wave Periods, T and Wind Velocity, u were calculated based on these relations. Because offshore engineering design requirements specify that loadings on a structure be based on at least 100-year return periods, the raw data obtained were insufficient for a direct estimation. For X 0, ( * X ) e F e (3) The corresponding cumulative frequency distribution model in equation (3) is used for shallow and water. Equations (4) and (5) have been adopted to obtain the cumulative frequency distribution for deep water. The 100 years occurrence probabilities for different sea states have been determined as relation with zero crossing periods and wind velocities. The predicted sea states will essentially contribute to the precise offshore structure design and implementation 25.

8 For X < 1.06, ( 2.44* X 2.224) e F e (4) For X > 1.06, ( 1.5* X ) e F e (5) 3. RESULTS AND DISCUSSION The wave height data provided by WorldWaves 21 and from the work done by Yaakob et al. 20 are considered raw in nature spanning a recording duration of 1 and 4 years respectively. This data period is considerably short for estimating the possible wave heights for a 100-year return period as required in offshore engineering design. That is why suitable wave height distribution models need to be constructed based on the available data in order to properly estimate the probability of higher sea wave height occurring in offshore locations in 100 years. The frequency mentioned in this section refers to the frequency of occurrence of a particular wave height, it should not be confused with the frequency (cycles/second) of a sinusoidal wave form. 3.1 Wave Height Distribution and occurrence probabilities The wave height frequency data collected was inputted and analyzed using the CumFreq program 23. It is capable of calculating the best-fitting cumulative (non-exceedance) frequency distribution of the input data series. The program tests various linear, logarithmic, exponential and double exponential cumulative frequency functions and selects the best fitting function automatically. Table 3. Frequency analysis on wave height distribution (Sarawak).

9 Table 4. Frequency analysis on wave height distribution (Terengganu). When the program detects a discontinuity in the function, it gives the user the choice to permit the introduction of a break point. The function fitting procedure starts with ranking the data (X) in ascending order and assigning rank frequencies Fr = R/ (N+1), where R is the rank number and N the total number of data. Next, linear regressions are made of Fr on the transformed data. The transformations are of a different kind corresponding to the type of function tried. The program also divides the range of X-data into a number (A) of equal intervals and calculates an interval frequency distribution. The number A can be selected by the user. To find the best cumulative distribution function to represent the wave height occurrence data, the program is set so that a break-point is allowed and may be taken account for, if it is detected. The break-point is found from the best-fit method. The wave data are analyzed by comparing how well it fits into the following frequency. Fig. 4. Zero Crossing Period and Wind Velocity relation with Significant Wave Height. The results from the frequency analysis done on the 1-year wave data offshore Terengganu and 4-year wave data offshore Sarawak are summarized in Table 3 and 4. Both of the wave data sources were found to be best fitted to a Gumbel frequency distribution, agreeing with the finding in some of the literature. Zero Crossing Period and Wind Velocity for the corresponding sea states have been shown in Fig. 4 as standalone. Table 5. Sea states with100-year probabilities for offshore Terengganu. Table 6. Sea states with100-year probabilities for offshore Sarawak. The 100 years occurrence probabilities for nine sea states are shown in Tables 5~6 as relation with zero crossing periods and wind velocities. The extracted data show that for initial sea state S1 the probability of occurrences is higher for Terengganu. But for larger wave heights the occurrence probabilities are significantly

10 larger for deep water in Sarawak location than the shallow water depth of Terengganu. 3.2 Return Period prediction The frequency analysis from the wave data clearly describes the mean wave heights and probability of occurrence. Tables 7~8 illustrate the detail information against return period. In addition the significant wave periods have also been generated as mention in the Table predicting the data up to 1000 years return period. For all the sea states the probability of occurrence is higher for deep water in Sarawak location than the shallow water depth of Terengganu for same return period. However, similar return period may experience sea wave of larger significant wave heights for shallow water depth in Terengganu. Table 7. Frequency Analysis of Wave Occurrence for Offshore Sarawak. Table 8. Frequency Analysis of Wave Occurrence for Offshore Terengganu. 4. CONCLUSION Offshore Terengganu, longitude 107 E, latitude 7 N and offshore Sarawak, longitude 111 E, latitude 6 N has been selected for wave data generation. The study essentially includes obtaining reliable sea wave data for the purpose of offshore engineering design. Wave height distribution is studied in detail to predict probability of occurrences of different sea states for 100-year return periods. Subsequently, wave data s for water depths of Terengganu and Sarawak basin, which is 200m (shallow) and 2000m (ultra-deep) respectively are developed. The developed data contributes 100-year probable wave heights and wave periods indicating the physical

11 properties of the sea including the wind velocity. Furthermore, wave characteristics of 1000 years return period are presented as well. Acknowledgments: The authors gratefully acknowledge University of Malaya, Malaysia for supporting this work through research grants RG093-10AET and PS B. References 1. M. Jameel, S. Ahmad, A. B. M. S. Islam, and M. Z. Jumaat, Proceedings of the 21 st International Offshore and Polar Engineering Conference, (2011) June 19-24; Maui, Hawaii, USA. 2. A. B. M. S. Islam, M. Jameel, and M. Z. Jumaat, International Journal of the Physical Sciences 6 (11), 2671 (2011). 3. M. Jameel and S. Ahmad, Proceedings of the ASME th International Conference on Ocean, Offshore and Arctic Engineering, OMAE (2011), June 19-24, Rotterdam, The Netherlands. 4. J.-W. Kim, C. Lee, and S. Park, Advanced Science Letters 4 (3), 696 (2011). 5. J. Rathmann and J. Jacobeit, Advanced Science Letters 2 (1), 1 (2009). 6. A. B. M. S. Islam, M. Jameel, and M. Z. Jumaat, International Journal of Green Energy, In Press, Corrected proof (2011). 7. O. Yaakob, N. Zainudin, Y. Samian, A. M. A. Malik, and R. A. Palaraman, Proceedings of the 1 st Asian Space Conference Chiang Mai, Thailand, E. Saleh, J. Beliku, T. Aung, and A. Singh, American Journal of Environmental Sciences 6 (3), 219 (2010). 9. M. Marghany and M. Hashim, International Journal of the Physical Sciences 5 (12), 1915 (2010). 10. A. Biswas and A. H. Kara, Advanced Science Letters 4 (1), 168 (2011).

12 11. H. W. Van den Brink, G. P. Konnen, J. D. Opsteegh, G. J. Van Oldenborgh, and G. Burgers, International Journal of Climatology 25 (10), 1345 (2005). 12. H. W. Van den Brink and G. P. Konnen, International Journal of Climatology 31 (1), 115 (2011). 13. H. W. Van den Brink and G. P. Konnen, Geophysical Research Letters 35 (23) (2008). 14. S. Caires and A. Sterl, Journal of Climate 18 (7), 1032 (2005). 15. S. Onni Suhaiza, S. Salim, and J. P. Frederik, The Journal of the Institution of Engineers, Malaysia 6 (1), 2671 (2007). 16. A. M. Muzathik, W. B. W. Nik, K. B. Samo, and M. Z. Ibrahim, Journal of Physical Science 22 (1), 77 (2011). 17. M. Jameel, S. Ahmad, A. B. M. S. Islam, and M. Z. Jumaat, Journal of Civil Engineering and Management, In press, Corrected proof (2011). 18. J. Lee, W.-B. Na, S. W. Shin, and D.-J. Kim, Advanced Science Letters 4 (4-5), 1702 (2011). 19. A. B. M. S. Islam, M. Jameel, M. Z. Jumaat, and S. M. Shirazi, International Journal of the Physical Sciences, In Press, Corrected proof (2011). 20. O. Yaakob, N. Zainudin, and R. A. Palaraman, Proceedings of the 26 th Asian Conference on Remote Sensing, Hanoi, Vietnam, WorldWaves, Fugro OCEANOR, Norway, The European Centre for Medium-Range Weather Forecasts (ECMWF) Wave Model (WAM). (2010). 22. PETRONAS, PETRONAS OIL & GAS COMPANY, Petroliam Nasional Berhad (2010). 23. T.L.T. How, BSc. Thesis, University of Malaya, Malaysia ( 2011). 24. N. A. Siddiqui and S. Ahmad, Reliability Engineering & System Safety 68 (3), 195 (2000). 25. M. Jameel, Ph.D. Thesis, Indian institute of technology Delhi, India ( 2008).

13 Figures and Tables Table 1. Four-year wave data for offshore Terengganu, 6-8 N, E. Table 2. One -year wave data for offshore Sarawak, 6 N, 111 E. Table 3. Frequency analysis on wave height distribution (Sarawak) Table 4. Frequency analysis on wave height distribution (Terengganu). Table 5. Sea states with100-year probabilities for offshore Terengganu. Table 6. Sea states with100-year probabilities for offshore Sarawak. Table 7. Frequency Analysis of Wave Occurrence for Offshore Sarawak. Table 8. Frequency Analysis of Wave Occurrence for Offshore Terengganu. Fig. 1. Mean seasonal significant wave heights over South China Sea, Peninsular Malaysia and Borneo. Fig. 2. Location of the Malaysian oil and gas blocks, with measured wave data locations. Fig. 3. South East Asian waters including contours for water depth. Fig. 4. Zero Crossing Period and Wind Velocity relation with Significant Wave Height.

14 Author(s): Mohammed Jameel, A.B.M. Saiful Islam, Firas A. Salman, M. Khaleel and M. Z. Jumaat Table 1. Four-year wave data for offshore Terengganu, 6-8 N, E 20. Significant Wave Heights, H s (m) Midpoint (m) Frequency of Occurrence Total: 1000 Table 2. One -year wave data for offshore Sarawak, 6 N, 111 E 21. Significant Wave Height, H s (m) Midpoint (m) Frequency of Occurrence Total: 1460

15 Table 3. Frequency analysis on wave height distribution (Sarawak). Summary: 1-year Sarawak wave height data (6 N, 111 E) Number of wave height data: 1460 Average: 1.29 Median: 1.04 Standard Dev.: The cumulative frequency function: Twice Gumbel Breakpoint : P = 1.06 Table 4. Frequency analysis on wave height distribution (Terengganu). Summary: 4-year Terengganu wave height data (7 N, 107 E) Number of wave height data: 1000 Average X: 1.10 Median X: 0.50 Std. Dev. of X: The cumulative frequency function: Generalized Gumbel Breakpoint : Breakpoint allowed but not found

16 Table 5. Sea states with100-year probabilities for offshore Terengganu. Sea State Significant Wave Height, H s (m) Occurrence Probability S E-01 S E-01 S E-01 S E-03 S E-05 S E-07 S E-09 S E-11 S E-14 Table 6. Sea states with100-year probabilities for offshore Sarawak. Sea State Significant Wave Height, H s (m) Occurrence Probability S E-02 S E-01 S E-01 S E-02 S E-03 S E-04 S E-05 S E-06 S E-07

17 Table 7. Frequency Analysis of Wave Occurrence for Offshore Sarawak. Return Period Significant Wave Heights Mean Wave Period Probability of Occurrence E E E E E E E E-07 Table 8. Frequency Analysis of Wave Occurrence for Offshore Terengganu. Return Period Significant Wave Heights Mean Wave Period Probability of Occurrence E E E E E-06

18 Author(s): Mohammed Jameel, A.B.M. Saiful Islam, Firas A. Salman, M. Khaleel and M. Z. Jumaat Fig. 1. Mean seasonal significant wave heights over South China Sea, Peninsular Malaysia and Borneo 21. Fig. 2. Location of the Malaysian oil and gas blocks, with measured wave data locations 22. Fig. 3. South East Asian waters including contours for water depth 21.

19 Fig. 4. Zero Crossing Period and Wind Velocity relation with Significant Wave Height.