基于数据挖掘技术的间歇采油模式优化

Wen Sun, Tao Ren, Xin Zhang, Hong Song
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引用次数: 1

摘要

为降低生产成本,低渗透油井常采用间歇采油方式。建立合理的间歇采油工作体系具有重要的意义。本文基于数据挖掘技术,通过一元非线性方程的回归分析,分别建立了间歇停运期和间歇抽运期动态液位高度随时间变化的数学模型。根据单位时间内的最大生产效率,确定采油指标。采用粒子群优化算法优化停泵时间,确定间歇采油模式。与其他间歇式采油方式的采油指标相比,该方法具有较好的采油效率和较高的经济效益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimization of intermittent oil production pattern based on data mining technology
In order to reduce production cost, intermittent oil production pattern is often used for low permeability oil wells. It is very important to establish the reasonable working system of intermittent oil production. In this paper, based on the data mining technology, through the regression analysis of monadic nonlinear equation, the mathematical model of the change of the dynamic liquid level height with time in intermittent shutdown period and intermittent pumping period are established respectively. According to the maximum production efficiency per unit time, the oil production index is determined. The particle swarm optimization algorithm is used to optimize the shutdown time of pump and determine the intermittent oil production pattern. Compared with the oil production index of other intermittent oil production patterns, this method has better oil production efficiency and higher economic benefits.
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