With the recent development of smart-well technology, the reservoir community now faces the challenge of developing robust and efficient techniques for reservoir characterization by means of data inversion. Unfortunately, classical history-matching methodologies do not possess computational efficiency and robustness needed to assimilate data measured almost in real time. Therefore, the reservoir community has started to explore techniques previously applied in other disciplines. Such is the case of the representer method, a variational data assimilation technique that was first applied in physical oceanography. The representer method is an efficient technique for solving linear inverse problems when a finite number of measurements are available. To the best of our knowledge, a general representer-based methodology for nonlinear inverse problems has not been fully developed. We fill this gap by presenting a novel implementation of the representer method applied to the nonlinear inverse problem of identifying petrophysical properties in reservoir models. Given production data from wells and prior knowledge of the petrophysical properties, the goal of our formulation is to find improved parameters so that the reservoir model prediction fits the data within some error given a priori. We first define an abstract framework for parameter identification in nonlinear reservoir models. Then, we propose an iterative representer-based scheme (IRBS) to find a solution of the inverse problem. Sufficient conditions for convergence of the proposed algorithm are established. We apply the IRBS to the estimation of absolute permeability in single-phase Darcy flow through porous media. Additionally, we study an extension of the IRBS with Karhunen-Loeve (IRBS-KL) expansions to address the identification of petrophysical properties subject to linear geological constraints. The IRBS-KL approach is compared with a standard variational technique for history matching. Furthermore, we apply the IRBS-KL to the identification of porosity, absolute and relative permeabilities given production data from an oil-water reservoir. The general derivation of the IRBS-KL is provided for a reservoir whose dynamics are modeled by slightly compressible immiscible displacement of two-phase flow through porous media. Finally, we present an ad-hoc sequential implementation of the IRBS-KL and compare its performance with the ensemble Kalman filter. / text

published_or_final_version / abstract / toc / Mechanical Engineering / Master / Master of Philosophy

published_or_final_version / Electrical and Electronic Engineering / Master / Master of Philosophy

published_or_final_version / Industrial and Manufacturing Systems Engineering / Master / Master of Philosophy

No description available.

The main objectives were: (1) to develop tools to aid in the design of enclosed agro-ecosystems, and (2) to use these tools to develop a prototype simulation-based control system. Three tools were developed: (1) a conceptual framework, (2) a (simulated) greenhouse system and (3) a simulation approach within OS/2. / Part of the conceptual framework was dedicated to "conscious control", defined as a form of control practised by an entity that uses models of itself in its decision-making processes. The greenhouse system was composed of six modules (a simulation manager, a weather generator, a greenhouse model, a crop model, a Pavlovian controller and a cognitive controller), which were implemented under OS/2 as separate processes. / The greenhouse system was used to develop a prototype simulation-based controller. Primarily, the role of the controller was to determine temperature setpoints that would minimize the heating load. The simulation model used by the controller was an artificial neural network. The controller adapted temperature setpoints to anticipated meteorological conditions and reduced greenhouse energy consumption, in comparison with a more traditional controller. / Generally, the results showed the feasibility and illustrated some of the advantages of using simulation-based control. The research resulted in the definition of elements that will allow the creation of a methodological framework for the design of simulation-based control and, eventually, a theory of conscious control.

No description available.

M.Ing. / This investigation explores the applicability of an adapted formal computational model for rapid synthesis of complete UAV (Unmanned Aerial Vehicle) systems in a single unified environment. The proposed framework termed XPDS (Cross-Platform Data Server) incorporates principles from a variety of similar, successful languages such as Giotto and Esterel. Application of such models has been shown to be advantageous in the UAV control system domain. The proposed solution extends the principles to the complete generic crafts/ground station problem and provides a unified framework for the development of distributed, scalable, and predictable solutions. The core of the framework is a hybrid FLET (Fixed Logical Execution Time) computational model which formalises the timing and operation of a number of concurrent processes or tasks. Three mechanisms are built upon the computational model – a design environment, simulation extensions, and code generation functionality. A design environment is proposed which permits a user to operate through an intuitive interface. The simulation extensions provide tight integration into established software such as Mathwork’s MatLab and Austin Meyer’s X-Plane. The code generation framework allows XPDS programs to be potentially converted into source for a variety of target systems. The combination of the three mechanisms and the formal computational model allow stakeholders to incrementally construct, test, and verify a complete UAV system. An implementation of the proposed framework is constructed to verify the proposed design. Initially, the implementation is subjected to a number of experiments that show that it is a valid representation of the specification. A simplified helicopter stability control system, based upon the problem statement from the initial literature review, is then presented as a test case and the solution is subsequently developed in XPDS. The scenario is successfully constructed and tested through the framework, demonstrating the validity of the proposed solution. The investigation demonstrates that it is both possible and beneficial to develop UAV systems in a single, unified environment. The incorporation of a formal computational model leads to rapid development of predictable solutions. The numerous systems are also easily integrated and benefit from features such as modularity and reusability.

D. Tech. (Department of Civil Engineering and Building, Faculty of Engineering and Technology), Vaal University of Technology / Growing demand for water due to increasing populations, industrialisation and water consuming lifestyles puts stress on existing water supply systems. To cater for the rising demand, water distribution networks are expanded beyond their design capacities and this creates transient “low-pressure-open-channel flow” (LPOCF) conditions. Current water supply models use “demand driven approach” (DDA) methodology which is not able to simulate transient LPOCF conditions, that poses an impediment to management/analysis of pressure-deficient networks. With a case study of the water supply network of Kampala City, LPOCF conditions were studied in this research. A “pressure/head driven approach” (PDA/HDA) was used in order to determine what demand is enabled by particular nodal pressures. Conversion of free surface to pressurised flow was analysed and modelled, with a view to clearly understanding occurrence of this phenomenon. The research demonstrated that if adequate pressures and flows are to be maintained, effectiveness of the water distribution network should be given as much attention as water production capacity. The research also indicated that when network pressures are low, the head-driven approach to water distribution modelling gives more accurate results than the traditional demand-driven methodology. Coexistence of free-surface and pressurised flow in networks prone to LPOCF conditions was confirmed and modelled. Results obtained highlighted the advantages of developing fully dynamic and transient models in the solution of transient LPOCF conditions in water distribution networks. Models developed allow application of PDA/HDA and DDA methodologies in systems that may exhibit LPOCF conditions thus enabling identification, understanding and analysis of the status of all sections of the network. These culminated in the development of a DSS to guide operational decisions that can be made to optimise network performance.

No description available.