基于数据的油藏生产过程设定点优化模型及算法研究

项目名称： 基于数据的油藏生产过程设定点优化模型及算法研究

项目编号： No.61463009

项目类型： 地区科学基金项目

立项/批准年度： 2015

项目学科： 自动化技术、计算机技术

项目作者： 龙文

作者单位： 贵州财经大学

项目金额： 47万元

中文摘要： 油藏生产过程优化控制理论与方法蕴藏着极大的经济效益且具有广阔的应用前景。目前对油藏生产过程的优化与控制大都基于大规模稳态模型，而对生产过程中注水率和产出率的设定点优化研究得较少。基于油藏生产过程中积累的注水率和产出率历史数据，本项目拟建立以注水率和产出率为决策变量的油藏生产过程设定点优化数学模型。目前，在利用智能优化算法求解设定点优化模型时，设计高效的智能优化算法和选择合适的约束处理技术没有可靠的方法和理论依据，且算法性能由两部分共同决定。本项目拟研究基于多样性设计的智能优化算法，以提高算法的全局搜索能力；根据问题自身领域知识和进化反馈信息指导选择和设计自适应个体比较与选择准则，以加快算法的收敛速度。研究基于智能优化算法的油藏生产过程设定点优化方法期望为油藏生产过程优化乃至更一般的复杂生产过程优化与控制提供实用有效的技术手段。

中文关键词： 油藏生产过程；设定点优化；优化模型；智能优化算法；约束处理技术

英文摘要： Optimization and control the oil reservoir production process have a wide application prospect, it can produces a great economic benefit. However, at present, optimization and control methods for oil reservoir production process are mostly based on the large scale steady-state model. Previous work do not provide any optimization procedure that systematically takes into account the interactions of an integrated oil and water production system and simultaneously optimizes the oil produced and water injected rates. In petroleum fields, injection and production rates are the most abundant data. In this research, an optimization problem for oil reservoir production process is formulated, where water injection rates and oil production rates are optimized simultaneously to maximize the future economic return of the reservoir asset. At present, there is no reliable guidance for how to develop the appropriate intelligent optimization algorithm and choose the suitable constraint-handling technique when solving a particular set point optimization problem. The performance of algorithm mainly depends on two components. One is the constraint-handling technique, and the other is the intelligent optimization algorithm. Motivated by these observations, this project aims to study intelligent optimization algorithms using diversified design in order to improve their global search capabilities. To accelerate the convergence speed of the algorithms, the selection and design of individual adaptive criteria will be guided by the domain knowledge inherent to the issue as well as the information obtained from evolutionary feedback. We will focus on the research of intelligent optimization algorithm-based constrained optimization method for oil reservoir set point, the method will provide a more practical and effective technology for set point optimization of oil reservoir production process and the optimization and control of general complex production process.

英文关键词： oil reservoir production process;set point optimization;optimization model;intelligent optimization algorithm;constraint-handling technique