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Author: | Hikari Fujii
| Year: | 1993
| Degree: | MS
| Adviser: | Horne
| File Size: | 4941 K
|
Abstract: Today, many oil and gas productiion systems have flowline networks with many wells and surface pipelines. In the design of such production systems, the determination of parameters like separator pressure, the diameter of tubing, pipeline, or surface choke, the length of pipeline, etc. has an extreme importance to the achievement of an optimum production rate.
The optimization of such problems, however, has been difficult due to the nonlinearity of the solution caused by the interaction between these parameters. In this work, multiple production parameters were optimized simultaneously in well networks in terms of the profit-based objective function such as total production rate, net income from the oil product, or present value discounted by interest rates. The techniques applied in this work were Newton-type methods (derivative based), the polytope method (function value based), and a new technique called Genetic Algorithms. After several test calculations of various types of optimization problems, the polytope method turned out to be the most efficient and consistent for low dimension problems with small numbers of wells, while the Genetic Algorithm showed an excellent performance in large systems with many variables to be optimized.
The production optimization of a pipeline network system was successfully achieved without any limitation on the selection of objective functions and decision variables to be optimized. The optimization technique can be used in the design stage of newly developed fields or the planning of workovers af existing fields. The combination of this technique with a reservoir simulation would also be a powerful tool in a project implementation design process.
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发表于 2014-2-10 16:59:59
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