基于智能计算的油田地面管网优化技术研究

发布时间：2018-01-25 14:17

本文关键词： 油田网络油气集输注水拓扑优化参数遗传算法模拟退火软件　出处：《大庆石油学院》2005年博士论文　论文类型：学位论文

【摘要】：规划设计是油田地面建设的依据,其设计质量的好坏直接影响到油田开发建设的经济效益。由于油田地面管网是涉及离散拓扑优化、非线性参数优化、多目标优化等在内的一类十分复杂的大型混合优化设计问题,其中有些子问题属于NP 难题,传统的优化设计方法难以获得较好的效果,导致目前油田地面管网仍旧停留在人工凭经验进行规划设计的阶段。随着优化技术的不断发展,以模拟退火、遗传算法、神经网络等为代表的智能计算方法以其高效的优化性能、无需问题特殊信息、具有全局搜索能力等优点,受到了各领域的广泛关注和应用,成为解决工程难解问题的有力工具,也为油田地面管网优化设计的有效解决提供了一定的手段。本文拟在对油田地面管网进行深入分析研究的基础上,采用智能计算技术,根据实际问题需求建立数学模型,通过设计适当的算法和编制相应的软件实现该系统的优化设计。论文主要从以下几个方面进行论述:　　首先,在对油田地面管网的结构特点、层次关系、网络变化特征等因素进行深入分析研究的基础上,运用图论等相关知识对地面管网中常见的MS 网络、MRS 网络和MST 网络进行了严格的数学定义。在此基础上,以网络系统投资和年运行费用最小为目标建立了这三种网络多目标规划设计的数学模型。采用计算复杂性理论对模型的计算难度进行了分析。根据模型的结构特点以及实际的规划设计过程,采取分层次优化策略,将模型求解分解为拓扑布局优化和参数优化两个子问题,两者之间通过迭代进行协调。其次,研究了油田地面管网拓扑布局优化问题。针对前面所建立的MS 网络、MRS 网络和MST网络,以管网系统投资最小为目标研究建立了相应的拓扑布局优化设计数学模型。根据模型的结构特点,提出采用分级优化法进行求解。该方法的优点是求解速度快、效率较高,但易于陷入局部优解。针对该方法的不足,将分级优化法、遗传算法和模拟退火算法有机地结合起来,形成了一种混合遗传模拟退火算法的求解策略。实例计算表明,该算法与分级优化法相比,在优化性能和初值鲁棒性等方面均有不同程度地提高。针对布局区域内存在障碍的问题,以MS 网络为例研究建立了障碍拓扑布局优化的二级混合规划模型,并提出混合遗传模拟退火算法的求解策略,给出了染色体的表达方式、可行性调整方法及评估计算方法,在实际应用中取得了较好效果。参数优化设计是管网规划设计中的一个重要问题。根据油气集输管网和注水管网的结构和工艺流程特点,采用流体力学理论推导了系统水力和热力分析计算方法。在此基础上,以降低管网投资和生产运行能耗为目的研究建立了这两个系统多目标参数优化设计的数学模型。该模型是包含离散变量和连续变量的大型混合优化设计问题。为了对模型进行有效求解,本文采用加权的方法首先将模型转化为单目标优化设计问题,然后采用混合遗传算法进行求解。实例计算表明了这种方法的有效性和可靠性。针对油田开发过程中地面工程系统的负荷率下降,效率降低,生产运行能耗升高的问题开展了研究。以生产运行能耗最小为目标研究建立了油气集输系统和注水系统生产运行方案优化问题的数学模型,并分别采用序列二次规划法和混合遗传算法进行求解,在实际应用中取得了良好的经济效益。最后,在以上理论研究工作的基础上,采用C++ Builder 语言编制完成了基于智能计算的油田地面管网规划设计和生产运行方案优化软件。应用该软件进行规划设计,不仅可以大大缩短规划方案编制周期,而且能够明显提高规划设计的质量,因而具有重要的应用和推广价值。
[Abstract]:Planning and design is the basis of oilfield surface construction, the quality of its design directly affects the economic benefit of the oilfield exploitation. Because oilfield pipeline network is related to discrete topology optimization, nonlinear parameter optimization, large mixed optimization design problem for a class of multiobjective optimization, is very complex, some of them belong to NP hard problems. Traditional optimization methods are difficult to obtain good results, leading to the current oilfield pipeline network is mainly based on the human experience of planning and design stage. With the continuous development of optimization technology, using simulated annealing, genetic algorithm, neural network as the representative of the calculation method for its high performance and no special information that has the advantage of global searching ability, has received widespread attention and application in various fields, has become a powerful tool for solving engineering problem, but also for the oil field Provides a means to optimize the design of the network effectively solve the surface. This article, based on the deep analysis of the oilfield pipeline network, using intelligent computing technology, the mathematical model is established according to the actual demand, optimize the design of the system through software design and programming corresponding appropriate algorithms. This paper mainly discusses from the following aspects:
First, at the level of structure characteristics of oilfield pipeline network relationship, based on the analysis of network characteristics and other factors, using graph theory and other related knowledge on common ground network MS network, MRS network and MST network is a mathematical definition. On this basis, the establishment of the three network the goal of the planning and design of mathematical model to minimize the network investment and operation cost as the goal. The difficulty in calculating the complexity of theoretical calculation for the model are analyzed. According to the structural characteristics of the model and practical design process, adopt hierarchic optimization strategy, the model is decomposed into two sub topology layout optimization and parameters optimization problem. Between the two are coordinated through iteration.
Secondly, study the topology layout optimization of oilfield pipeline network is established. According to the MS network, MRS network and MST network, the network system of investment objective is to minimize the research established a mathematical model of optimization design of topology layout accordingly. According to the structural characteristics of the model, hierarchical optimization is adopted. The advantage of this method is the solution speed, higher efficiency, but is easy to fall into local optimal solution. Because of the deficiency of this method, the hierarchical optimization method, genetic algorithm and simulated annealing algorithm are combined, the formation of a hybrid genetic simulated annealing algorithm solving strategy. The calculation results show that compared with the algorithm of hierarchical optimization method, have different degree to improve the optimization performance and initial robustness. Aiming at the existing problems in the distribution area, the MS network as an example of topological layout optimization two A hybrid programming model is proposed, and the solving strategy of the hybrid genetic simulated annealing algorithm is proposed. The expression method, feasibility adjustment method and evaluation method of the chromosome are presented, which has achieved good results in practical applications.
Parameter optimization design is an important problem in network design. According to the structure and process characteristics of oil and gas pipeline and water injection pipe set, using the theory of fluid mechanics is the hydraulic and thermal system analysis method. On this basis, in order to reduce the network investment and production energy consumption established a mathematical model of multi-objective optimization the design parameters of the two systems for the purpose of research. The model is a hybrid optimization design problem with discrete and continuous variables. In order to solve the model, this paper will be transformed into a single objective optimization problem by using the weighted method, and then solved by the hybrid genetic algorithm. The calculation results show that the model is effective and reliability of this method.
To reduce surface engineering in the process of oilfield development system load rate, efficiency, high operation energy consumption is studied. The minimal energy consumption in operation as a mathematical model for optimization operation of transmission system and water injection system of oil and gas gathering scheme is established, and using the sequence of two quadratic programming method and hybrid genetic algorithm, and achieved good economic benefits in practical application.
Finally, based on the theoretical research results, using C++ Builder language to complete the preparation of software optimization of oilfield pipeline network planning design and operation scheme based on Intelligent Computing. Planning and design of the application, not only can greatly shorten the period of planning and design, and can greatly improve the design quality, which has important the application and promotion of value.

【学位授予单位】：大庆石油学院
【学位级别】：博士
【学位授予年份】：2005
【分类号】：TE42

【引证文献】