摘要
在对灰色模型进行研究的基础上,对其进行了改进,使其适用范围更加广泛,并利用遗传算法的强大 搜索功能计算参数λ。建立模型时采用油气井日产量的累加序列作为基础数据,这样就弱化了原始数据的随机波 动性,强化了其规则有序性,而生成的一阶累加序列能列好地满足灰指数规律,适用于改进的GM(1,1)模型。计算 实例表明,该模型所需原始数据少,预测精度高,操作方便,具有一定的实用价值。
On the basis of study of the grey model, the paper presented the improved model. The new one can be used in more wide fields. The parameter is calculated by the genetic algorithm, which has powerful search function. The data used in the model are accumulated sequence of daily oil production rate, so that the generated one become more regular, and it satisfied grey exponential law, as is suitable for the improved grey model of GM(1,1). It has been testified by field case that the model needs less source data, but its prediction precision is relatively high. The new method is very simple to use, so it has a good value in oil field.
出处
《钻采工艺》
CAS
北大核心
2005年第1期42-44,共3页
Drilling & Production Technology
基金
本文系四川省重点实验室基金项目(省室基金015)的部分成果。
关键词
灰色模型
遗传算法
可采储量
grey model, genetic algorithm, recoverable reserve