New Method of Productivity Prediction by Fitting of IPR Curve

被引：0

作者：

Fan, Ling ^{[1
]}

Yue, Baolin ^{[1
]}

Liu, Chao ^{[1
]}

Sui, Yiyong ^{[1
]}

机构：

[1] China Univ Petr, Sch Petr Engn, Dongying, Shandong 257061, Peoples R China

来源：

2011 INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND NEURAL COMPUTING (FSNC 2011), VOL V | 2011年

关键词：

Bendakhlia Model; IPR curve; Genetic Algorithm;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Due to the limitations of theoretical IPR Models, though many methods of modification are developed, the general IPR Model fitted by various oil field is difficult to be obtained. According to the tested results obtained by various oil well in different reservoirs, using Genetic Algorithm combine with the Bendakhlia model, the paper present a dynamical fitting method of IPR curve to predict the production fitted the model parameter in various reservoirs conditions. According to calculating the knee of IPR curve, the appropriate range of application can be confirmed. On the basis of this research, the IPR fitting program is developed. And the simulation results are contrasted with the measured data at site. The contrast results demonstrate that the computational results are accurate and reliable. So it can be used in prediction and conforming the appreciate production in oil well.

引用

页码：1 / 4

页数：4