A truss spar, named as Horn Mountain, was deployed in the Gulf of Mexico in 1,650 m of water, approximately 150 km southeast of New Orleans in June 2002. Horn Mountain is operated by British Petroleum (B.P.). Extensive field measurements were made using an integrated marine monitoring system attached to the truss spar. In this study, dynamic analysis of the truss spar interacting with its mooring and riser system was performed using a time-domain numerical code, known as ‘COUPLE’. The simulated results were then compared with the corresponding field measurements made during Hurricane Isidore. During the numerical study, various hydrodynamic parameters which were crucial to the accuracy of predicting the global motions of the truss spar and tensions in mooring lines and risers were scrutinized, such as the drag and added-mass coefficients of heave plates, hard tank and truss beams. Satisfactory agreement between the simulation and corresponding measurements was reached, indicating that the numerical code, COUPLE, can be used to conduct the time-domain analysis of a truss spar interacting with its mooring and riser system under severe storm impact. A comparative study was also conducted to analyze the significance of interaction of risers with the hull structure. Three different cases of coupled analysis are simulated, namely (i) coupled analysis of truss spar interacting with mooring lines, (ii) coupled analysis of truss spar interacting with the mooring lines and the steel catenary risers, (iii) coupled analysis of truss spar interacting with the mooring lines, the steel catenary risers and top tension risers. Major statistical parameters of the global motions of the truss spar and the mooring line tensions for the three cases are compared with the field measurements.

Due to its increasing popularity, hierarchical linear modeling (HLM) has been used along with structural equation modeling (SEM) to analyze data with nested structure. In spite of the extensive research on commonly encountered problems such as violation of normality and missing data treatment within the framework of SEM, these areas have been much less explored in HLM. The present study compared HLM and multilevel SEM through a Monte Carlo study from the perspectives of the influence of nonnormality and performance of multiple imputation based on the expectationmaximization (EM) algorithm under various combinations of sample sizes at two levels. The statistical power, parameter estimates, standard errors, and estimation bias for the main effects and cross-level interaction in a two- level model were compared across the four design factors: analysis method, normality condition, missing data proportion, and sample size. HLM and multilevel SEM appeared to have similar power detecting the main effect, while HLM had better power for the cross- level interaction. Neither seemed to be sensitive to violation of the normality assumption. A higher proportion of missing data resulted in larger standard errors and estimation bias. Sample sizes at both the individual and cluster levels played a role in the statistical power for parameter estimates. The two-way interactions for the four factors were generally nonzero. Overall, both HLM and multilevel SEM were quite robust to violation of normality. SEM appears more useful in more complex path models while HLM is superior in detecting main effects. Multiple imputation based on the EM algorithm performed well in producing stable parameter estimates for up to 30% missing data. Sample size design should take into account the level at which the research is most focused.

The purpose of this thesis is to develop and demonstrate a physically based rigid body simulation with a focus on simplifications to achieve real-time performance. This thesis aims to demonstrate that by improving the efficiency with simplified calculations of possible bottlenecks of a real-time rigid body simulation, the accuracy can be improved. A prototype simulation framework is implemented to evaluate the simplifications. Finally, various real-time rendering features are implemented to achieve a realistic look, and also to imitate the game-like environment where real-time rigid body simulations are mostly utilized. A series of demonstration experiments are used to show that our simulator does, in fact, achieve real-time performance, while maintaining satisfactory accuracy. A direct comparison of this prototype with a commercially available simulator verifies that the simplified approach improves the efficiency and does not damage the accuracy under our test conditions. Integration of rendering elements like advanced shading, shadowing, depth of field and motion blur into our real-time framework also enhanced the perception of simulation outcomes.

In many cases, it is important to predict water production performance of oil wells early in, or maybe before, their production life. In as much as oil field water is important for pressure maintenance purposes and displacement of oil towards the perforation of the producing well, excessive water production leads to increased cost. In the case when no provision is made, it represents a significant liability. The case considered here is a well producing from a monocline with an edge-water aquifer. Although such problems can be computed with reservoir simulation, the objective of this work was to develop an empirical method of making water production predictions. The reservoir model was described as a single well producing from the top of a monocline drainage block with water drive from an infinite-acting aquifer. During the reservoir simulation runs, water would cusp and cone into the well, increasing water production and decreasing oil production. A number of simulation runs were made, varying eleven model variables. Typical model variables include dip angle, formation thickness and production rate. For each run a modified Addington-style plot was made. The relationship between each model parameter and three graphical variables was used to develop the set of empirical correlations. The empirical correlations developed were integrated with some derived equations that relate important reservoir parameters and incorporated into a computer program. The developed correlations and program can be used to carry out sensitivity analysis to evaluate various scenarios at the early planning stages when available reservoir data are limited. This gives a quick and easy method for forecasting production performance with an active edge-water drive. Furthermore, the approach developed in the research can be applied to other water production problems in other fields/reservoirs. The developed program was validated and used to evaluate synthetic and field cases. Overall, a good match was achieved.

Integrated reservoir modeling has become an important part of day-to-day decision analysis in oil and gas management practices. A very attractive and promising technology is the use of time-lapse or 4D seismic as an essential component in subsurface modeling. Today, 4D seismic is enabling oil companies to optimize production and increase recovery through monitoring fluid movements throughout the reservoir. 4D seismic advances are also being driven by an increased need by the petroleum engineering community to become more quantitative and accurate in our ability to monitor reservoir processes. Qualitative interpretations of time-lapse anomalies are being replaced by quantitative inversions of 4D seismic data to produce accurate maps of fluid saturations, pore pressure, temperature, among others. Within all steps involved in this subsurface modeling process, the most demanding one is integrating the geologic model with dynamic field data, including 4Dseismic when available. The validation of the geologic model with observed dynamic data is accomplished through a "history matching" (HM) process typically carried out with well-based measurements. Due to low resolution of production data, the validation process is severely limited in its reservoir areal coverage, compromising the quality of the model and any subsequent predictive exercise. This research will aim to provide a novel history matching approach that can use information from high-resolution seismic data to supplement the areally sparse production data. The proposed approach will utilize streamline-derived sensitivities as means of relating the forward model performance with the prior geologic model. The essential ideas underlying this approach are similar to those used for high-frequency approximations in seismic wave propagation. In both cases, this leads to solutions that are defined along "streamlines" (fluid flow), or "rays" (seismic wave propagation). Synthetic and field data examples will be used extensively to demonstrate the value and contribution of this work. Our results show that the problem of non-uniqueness in this complex history matching problem is greatly reduced when constraints in the form of saturation maps from spatially closely sampled seismic data are included. Further on, our methodology can be used to quickly identify discrepancies between static and dynamic modeling. Reducing this gap will ensure robust and reliable models leading to accurate predictions and ultimately an optimum hydrocarbon extraction.

This thesis presents a method to implement a hybrid particle/grid uid simulation on graphics hardware. The goal is to speed up the simulation by exploiting the parallelism of the graphics processing unit, or GPU. The Fluid Implicit Particle method is adapted to the programming style of the GPU. The methods were implemented on a current generation graphics card. The GPU based program exhibited a small speedup over its CPU based counterpart.

Molecular dynamics simulations were conducted on a system consisting of a decamer DNA solvated by trehalose and water (molecular ratio= 1:2), to mimic a relatively dry state for the DNA molecule. Simulations were performed at two different temperatures, 300 K and 450 K. The B-form DNA structure was shown to be stable at both temperatures. The analysis of hydrogen bonds between trehalose/water and DNA revealed that trehalose and backbone DNA formed the largest number of hydrogen bonds and thus constituted the major effect of structural protection for DNA. The number of hydrogen bonds formed by each OH group of trehalose with the backbone DNA was compared. Different types of trehalose-DNA interactions were analyzed, with no prevalent pattern recognized. Diffusion constants for trehalose and water were also calculated, suggesting a glassy/viscose state of the simulation system. It is believed that trehalose protects DNA in the dry state through the network of hydrogen bonds built by the sugars, which reduces the structural fluctuations of DNA and prevents its denaturation.

The development of coarsened reservoir simulation models from high resolution geologic models is a critical step in a simulation study. The optimal coarsening sequence becomes particularly challenging in a fluvial channel environment where the channel sinuosity and orientation can result in pay/non-pay juxtaposition in many regions of the geologic model. The optimal coarsening sequence is also challenging in tight gas sandstones where sharp changes between sandstone and shale beds are predominant and maintaining the pay/non-pay distinction is difficult. Under such conditions, a uniform coarsening will result in mixing of pay and non-pay zones and will likely result in geologically unrealistic simulation models which create erroneous performance predictions. In particular, the upgridding algorithm must keep pay and non-pay zones distinct through a non-uniform coarsening of the geologic model. We present a coarsening algorithm to determine an optimal reservoir simulation grid by grouping fine scale geologic model cells into effective simulation cells. Our algorithm groups the layers in such a way that the heterogeneity measure of an appropriately defined static property is minimized within the layers and maximized between the layers. The optimal number of layers is then selected based on an analysis resulting in a minimum loss of heterogeneity. We demonstrate the validity of the optimal gridding by applying our method to a history matched waterflood in a structurally complex and faulted offshore turbiditic oil reservoir. The field is located in a prolific hydrocarbon basin offshore South America. More than 10 years of production data from up to 8 producing wells are available for history matching. We demonstrate that any coarsening beyond the degree indicated by our analysis overly homogenizes the properties on the simulation grid and alters the reservoir response. An application to a tight gas sandstone developed by Schlumberger DCS is also used in our verification of our algorithm. The specific details of the tight gas reservoir are confidential to Schlumberger's client. Through the use of a reservoir section we demonstrate the effectiveness of our algorithm by visually comparing the reservoir properties to a Schlumberger fine scale model.

Thèse de doctorat : Mécanique : Ecully, Ecole centrale de Lyon : 2007. / Titre provenant de l'écran-titre. 150 références.

Thèse de doctorat : Mécanique : Ecully, Ecole centrale de Lyon : 2007. / 150 références.