This thesis presents the results of a study on the effects of marine growth on the hydrodynamic loading of offshore structures and proposes an approach that can be adopted by designers and operators to quantify these effects. The approach is based upon the realistic characterisation of marine growth and its temporal variations during the life span of template structures. Past research work and current design, inspection and maintenance practices are critically reviewed and their limitations with respect to marine growth are highlighted. The ecology of marine growth for a sample of North Sea platforms was examined to establish the variety and physical attributes of the fouling colonies. The traditional single-parameter characterisation of marine roughness was found to be inadequate. Appropriate parameters, verified by fluid loading experiments, are established. Details of the laboratory experiments undertaken with both real marine growth and artificial macro-roughness on circular cylinders are given. These tests were carried out at large scale (cylinders up to 521mm diameter) in a novel "buoyant cylinder" test rig (steady flow) and in a large wave flume (regular waves). A wide range of parametric variations were undertaken for the various types of marine growth in an attempt to establish a comprehensive database from which the loading effect of any likely, practically occuring, marine growth pattern can be estimated. The extent to which this is achieved and the requirements for further research are discussed in detail. It is concluded that the effects of marine growth are both substantial and diverse. Drag forces vary with type of fouling, overall thickness, surface cover, and distribution. Finally, detailed procedures are recommended for the design of new structures and the improved loading assessment of existing ones.

This study provides the physical, mathematical and numerical basis of analysis work performed for predicting the flow around three-dimensional bluff body configurations. The flow has been treated as steady, incompressible, turbulent. The predictions were made using a two-equation turbulence model, solving transport equations for turbulence kinetic energy K and the turbulence dissipation rate ε, in addition to the partial differential equations for the conservation of mass and momentum. The program used was the well tested computer code "PHOENICS-84" based on work conducted by Prof. D.B. Spalding and Co-workers. Several computations have been performed, for three models: a single cube, a pair of cubes with different spacing, and a rudimentary representation of an offshore oil platform stucture. The prediction procedure was first tested for grid refinement and optimum solution domain size until profiles at several locations for selected variables showed little change with further increase of domain size and grid points. The effect of different wind directions was investigated for the three models; in addition, different pitching conditions of the oncoming flow were also considered for the platform-model configurations. Comparisons were made with wind tunnel test results on the same three models, and some discrepancies are noted, particularly in regions of separated, recirculating flow. Also comparisons were made with certain empirical calculation procedures used for wind load estimation in maritime engineering. Overall wind loading is nevertheless reasonably well predicted. Applications of the method in the area of wind loadings on a full scale offshore oil rig is discussed, and plans for refinement and extension of the present work are outlined. It is concluded that the present method can be used as a suitable starting point for generating a platform aerodynamics simulator. However, more work is required to this end, in order to represent adequately all aspects of platform-aerodynamics phenomena.

Notwithstanding that civil liability for pollution damage as well as compensation is emphatically recognised and established under international treaty, there is a conspicuous absence of a single comprehensive regional framework as well as universal treaty that address this issue with regards to offshore oil and gas exploration. The reason for this might not be unconnected to the occasional occurrence of offshore platform and oil well blowouts. Meanwhile, offshore operations pose a constant threat to the marine environment particularly in the face of new and continuous technological advancement as well as human quest for energy-oil supply, which has encouraged ultra deep exploration of oil and gas, therefore making ecological disaster imminent. The adoption of regional arrangement has been the trend adopted to tackle this predicament and this has been made more pronounced by the International Maritime Organisation (IMO) by its declaration that ‘as much as bilateral and regional agreements are in view, global one is not’ coupled with the deafening silence of other related United Nations’ organs on the issue. So in the light of this, this study argues that Africa’s single and comprehensive regional treaty on offshore oil rig regulation is long overdue. / Dissertation (LLM)--University of Pretoria, 2014. / gm2015 / Centre for Human Rights / LLM / Unrestricted

The failure of oil well drillstrings due to torsional and longitudinal stresses caused by stick-slip phenomena during the drilling operation causes great expense to industry. Due to the complicated and harsh drilling environment, modelling of the drillstring becomes an essential requirement in studies. Currently, this is achieved by modelling the drillstring as a torsional lumped model (which ignores the length of the drillstring) for real-time measurement and control. In this thesis, a distributed-lumped model including the effects of drillstring length was developed to represent the drillstring, and was used to simulate stick-slip vibration. The model was developed with increasing levels of detail and the resultant models were validated against typical measured signals from the published literature. The stick-slip model describes the friction model that exists between the cutting tool and the rock. Based on theoretical analysis and mathematical formulation an efficient and adaptable model was created which was then used in the application of a method of species conserving genetic algorithm (SCGA) to optimise the drilling parameters. In conclusion, it was shown that the distributed-lumped model showed improved detail in predicting the transient response and demonstrated the importance of including the drillstring length. Predicting the response of different parameters along the drillstring is now possible and this showed the significant effect of modelling the drillcollar. The model was shown to better represent real system and was therefore far more suited to use with real time measurements. / Iraqi Government, Ministry of Higher Education and Scientific Research.

Nous présentons dans cette thèse en premier lieu la méthode de Bootstrap par permutation appliquée à la méthode des blocs maxima utilisée en théorie des valeurs extrêmes (TVE) univariée. La méthode est basée sur un échantillonnage particulier des données en utilisant les rangs des blocs maxima dont la distribution est présentée et introduite dans les simulations. Elle amène à une réduction de la variance des paramètres de la loi GEV et des quantiles estimés. En second lieu, on s’intéresse au cas où les observations sont indépendantes mais non identiquement distribuées en TVE. Cette variation dans la distribution est quantifiée en utilisant une fonction dite « skedasis function » notée c qui représente la fréquence des extrêmes. Ce modèle a été introduit par Einmahl et al. dans le papier « Statistics of heteroscedastic extremes ». On étudie plusieurs modèles paramétriques pour c (log-linéaire, linéaire, log-linéaire discret) ainsi que les résultats de consistance et de normalité asymptotique du paramètre θ représentant la tendance. Le test θ =0 contre θ ≠0 est interprété alors comme un test de détection de tendance dans les extrêmes. Nous illustrons nos résultats dans une étude par simulation qui montre en particulier que les tests paramétriques sont en général plus puissants que les tests non paramétriques pour la détection de la tendance, d’où l’utilité de notre travail. Nous discutons en plus le choix du seuil k en appliquant la méthode de Lepski. Enfin, nous appliquons la méthodologie sur les données de températures minimales et maximales dans la région de Fort Collins, Colorado durant le 20ème siècle afin de détecter la présence d’une tendance dans les extrêmes sur cette période. En troisième lieu, on dispose d’un jeu de données de précipitation journalière maximale sur 24 ans dans 40 stations. On réalise une prédiction spatio-temporelle des quantiles correspondants à un niveau de retour de 20 ans pour les précipitations mensuelles dans chaque station. Nous utilisons des modèles de GEV en introduisant des covariables dans les paramètres. Le meilleur modèle est choisi en termes d’AIC et par la méthode de validation croisée. Pour chacun des deux modèles choisis, nous estimons les quantiles extrêmes. Finalement, on applique la TVE unvariée et bivariée sur les vitesses du vent et la hauteur des vagues dans une région au Liban en vue de protéger la plateforme pétrolière qui y sera installée de ces risques environnementaux. On applique d’abord la théorie univariée sur la vitesse du vent et la hauteur des vagues séparément en utilisant la méthode des blocs maximas pour estimer les paramètres de la GEV et les niveaux de retour associés à des périodes de retour de 50, 100 et 500 années. Nous passons ensuite à l’application de la théorie bivariée afin d’estimer la dépendance entre les vents et les vagues extrêmes et d’estimer des probabilités jointes de dépassement des niveaux de retour univariés. Nous associons ces probabilités jointes de dépassement à des périodes de retour jointes et nous les comparons aux périodes de retour marginales. / We firstly present in this thesis the permutation Bootstrap method applied for the block maxima (BM) method in extreme value theory. The method is based on BM ranks whose distribution is presented and simulated. It performs well and leads to a variance reduction in the estimation of the GEV parameters and the extreme quantiles. Secondly, we build upon the heteroscedastic extremes framework by Einmahl et al. (2016) where the observations are assumed independent but not identically distributed and the variation in their tail distributions is modeled by the so-called skedasis function. While the original paper focuses on non-parametric estimation of the skedasis function, we consider here parametric models and prove the consistency and asymptotic normality of the parameter estimators. A parametric test for trend detection in the case where the skedasis function is monotone is introduced. A short simulation study shows that the parametric test can be more powerful than the non-parametric Kolmogorov-Smirnov type test, even for misspecified models. We also discuss the choice of threshold based on Lepski's method. The methodology is finally illustrated on a dataset of minimal/maximal daily temperatures in Fort Collins, Colorado, during the 20th century. Thirdly, we have a training sample data of daily maxima precipitation over 24 years in 40 stations. We make spatio-temporal prediction of quantile of level corresponding to extreme monthly precipitation over the next 20 years in every station. We use generalized extreme value models by incorporating covariates. After selecting the best model based on the Akaike information criterion and the k-fold cross validation method, we present the results of the estimated quantiles for the selected models. Finally, we study the wind speed and wave height risks in Beddawi region in the northern Lebanon during the winter season in order to protect the oil rig that will be installed. We estimate the return levels associated to return periods of 50, 100 and 500 years for each risk separately using the univariate extreme value theory. Then, by using the multivariate extreme value theory we estimate the dependence between extreme wind speed and wave height as well as joint exceedance probabilities and joint return levels to take into consideration the risk of these two environmental factors simultaneously.