Offshore Structure Specific Performance Targets

2021 ◽  
Author(s):  
Mohamed Atia ◽  
Ahmed Abdelkhalek ◽  
Anjan Sarkar ◽  
Matt Keys ◽  
Mahesh Patel ◽  
...  
Keyword(s):  
Offshore Structures ◽  
Considerable Improvement ◽  
Machine Learning Algorithms ◽  
Water Current ◽  
Extreme Value Analysis ◽  
Specific Response ◽  
Offshore Structure ◽  
Specific Criterion ◽  
Value Analysis ◽  
Hazard Ratios

Abstract Offshore structures exist in the harshest environments and each region is unique in the severity and development of extreme weathers. This had led to challenges in the identification of a single criterion that's internationally applicable. ADNOC Offshore and Kent, formerly Atkins Oil and Gas, worked closely in 2010 to develop a high-level generalised regional criterion for the Arabian Gulf and in 2020, a major project was conducted to develop a structure-specific criterion that resulted in considerable improvement in risk levels and financial gains. For each of ADNOC Offshore's 480 structures, a Response Based Metocean Analysis (RBMA) was conducted adopting Tromans and Vanderschuren (1995) approach. Structure specific hindcast data at 3-hour intervals over a period of 37 years was analysed, isolating storms and executing hydrodynamic analyses considering joint environmental conditions. Through adopting a combination of peak-over-threshold method and Markov-Chain-Monte-Carlo (MCMC) simulations, convolution of long-term (storms) and short-term (wave probabilities within a storm) was conducted resulting in the generation of the Hazard Curves that account for the possible uncertainties associated with variations in each of the distributions. The structure specific response based metocean analysis resulted in a considerable improvement in the criteria for ADNOC Offshore’s structures. The resulting Hazard Curve ratios (10,000-year to 100-year response parameter ratio) for approximately 95% of the structures were evaluated lower as compared to the 2010 generalised study. It was observed that the water current profiles had a significant impact on the hazard ratios, and specially for assets in the vicinity of the islands. Based on the resulting hazard ratios a detailed risk assessment was conducted and compliance and life extension of most of ADNOC Offshore structures was justified without the need for physical strengthening of their assets. Through the use of machine-learning algorithms associated with serval statistical sampling techniques, extreme value analysis was conducted in conjunction with the MCMC approach and resulted in what is likely to be the largest offshore fleet application of the method.

Reevaluation of Design Waves Off the Western Indian Coast Considering Climate Change

2016 ◽  
Vol 50 (1) ◽  
pp. 88-98 ◽  
Author(s):  
Pentapati Satyavathi ◽  
Makarand C. Deo ◽  
Jyoti Kerkar ◽  
Ponnumony Vethamony
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
General Circulation ◽  
Generalized Pareto Distribution ◽  
Circulation Model ◽  
Offshore Structures ◽  
Future Climate Change ◽  
Extreme Value Analysis ◽  
Value Analysis ◽  
Wave Data

AbstractKnowledge of design waves with long return periods forms an essential input to many engineering applications, including structural design and analysis. Such extreme or long-term waves are conventionally evaluated using observed or hindcast historical wave data. Globally, waves are expected to undergo future changes in magnitude and behavior as a result of climate change induced by global warming. Considering future climate change, this study attempts to reevaluate significant wave height (Hs) as well as average spectral wave period (Tz) with a return period of 100 years for a series of locations along the western Indian coastline. Historical waves are simulated using a numerical wave model forced by wind data extracted from the archives of the National Center for Environmental Prediction and the National Center for Atmospheric Research, while future wave data are generated by a state-of-the-art Canadian general circulation model. A statistical extreme value analysis of past and projected wave data carried out with the help of the generalized Pareto distribution showed an increase in 100-year Hs and Tz along the Indian coastline, pointing out the necessity to reconsider the safety of offshore structures in the light of global warming.

Response-based extreme value analysis of moored offshore structures due to wave, wind, and current

1998 ◽  
Vol 3 (3) ◽  
pp. 145-150 ◽  
Author(s):  
Atiela Incecik ◽  
John Bowers ◽  
Gill Mould ◽  
Oguz Yilmaz
Keyword(s):  
Offshore Structures ◽  
Extreme Value ◽  
Extreme Value Analysis ◽  
Value Analysis

A Comparison of Methods for Assessing the Lifetime Reliability of a Moored FPSO

2004 ◽  
Author(s):  
Andrew J. Grime ◽  
R. S. Langley
Keyword(s):  
Reliability Analysis ◽  
Offshore Structures ◽  
Extreme Value Analysis ◽  
Design Codes ◽  
Short Term ◽  
Safety Level ◽  
Value Analysis ◽  
Design Storm ◽  
Current Design

Current design codes for floating offshore structures are based on measures of short-term reliability. That is, a design storm is selected via an extreme value analysis of the environmental conditions and the reliability of the vessel in that design storm is computed. Although this approach yields valuable information on the vessel motions, it does not produce a statistically rigorous assessment of the lifetime probability of failure. An alternative approach is to perform a long-term reliability analysis in which consideration is taken of all sea states potentially encountered by the vessel during the design life. Although permitted as a design approach in current design codes, the associated computational expense generally prevents its use in practice. A new efficient approach to long-term reliability analysis is presented here, the results of which are compared with a traditional short-term analysis for the surge motion of a representative moored FPSO in head seas. This serves to illustrate the failure probabilities actually embedded within current design code methods, and the way in which design methods might be adapted to achieve a specified target safety level.

Stochastic Space-Time Extremes of Wind Sea States: Validation and Modeling

2014 ◽  
Author(s):  
Francesco Barbariol ◽  
Alvise Benetazzo ◽  
Filippo Bergamasco ◽  
Sandro Carniel ◽  
Mauro Sclavo
Keyword(s):  
Time Domain ◽  
Stochastic Models ◽  
Ocean Waves ◽  
Offshore Structures ◽  
Gaussian Random Fields ◽  
Space Time ◽  
Extreme Value Analysis ◽  
Physical Parameters ◽  
Value Analysis ◽  
Field Evidence

Damages and accidents occurred to offshore structures and routing ships raise questions about adequacy of conventional time domain analysis of short-crested sea waves. Indeed, experimental and field evidence showed that during such wave states, typical of storms, the maximum sea surface elevation gathered at a single point in time, i.e. the time extreme, tends to underestimate the actual maximum that occurs over a surrounding area, i.e. the space-time extreme. Recently, stochastic models for the prediction of multidimensional Gaussian random fields maxima, e.g. Piterbarg’s theorem and Adler and Taylor’s approach, have been applied to ocean waves statistics, permitting to extend extreme value analysis from time to space-time domain. In this paper, we present analytical and numerical approaches aimed at supporting applicability of such models, which is limited by the knowledge of directional spectrum parameters. Firstly, we validate stochastic models against stereo-photogrammetric measurements of surface wave fields. Then, we investigate the dependence of space-time extremes upon physical parameters (wind speed, fetch length, current speed) in the context of analytical spectral formulations, i.e. Pierson-Moskowitz and JONSWAP, and by using spectral numerical wave modeling. To this end, we developed two sets of closed formulae and a modified version of the SWAN model to calculate parameters of analytical and arbitrary directional spectra, respectively. Finally, we present preliminary results of a 3 years Mediterranean Sea hindcast as a first step towards operational forecasts of space-time extremes.

Modeling European hot spells using extreme value analysis

2014 ◽  
Vol 58 (3) ◽  
pp. 193-207 ◽  
Author(s):  
C Photiadou ◽  
MR Jones ◽  
D Keellings ◽  
CF Dewes
Keyword(s):  
Extreme Value ◽  
Extreme Value Analysis ◽  
Value Analysis ◽  
Hot Spells

scholarly journals Threshold selection in univariate extreme value analysis

Extremes ◽  
2021 ◽  
Author(s):  
Laura Fee Schneider ◽  
Andrea Krajina ◽  
Tatyana Krivobokova
Keyword(s):  
Mean Squared Error ◽  
Extreme Value ◽  
Hill Estimator ◽  
Small Samples ◽  
Extreme Value Analysis ◽  
Threshold Selection ◽  
Value Analysis ◽  
Wide Range ◽  
Asymptotic Mean Squared Error ◽  
The Hill

AbstractThreshold selection plays a key role in various aspects of statistical inference of rare events. In this work, two new threshold selection methods are introduced. The first approach measures the fit of the exponential approximation above a threshold and achieves good performance in small samples. The second method smoothly estimates the asymptotic mean squared error of the Hill estimator and performs consistently well over a wide range of processes. Both methods are analyzed theoretically, compared to existing procedures in an extensive simulation study and applied to a dataset of financial losses, where the underlying extreme value index is assumed to vary over time.

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