A model for estimation of permeability and free flowing porosity

被引：5

作者：

Barati-Harooni, Ali ^{[1
]}

Najafi-Marghmaleki, Adel ^{[1
]}

Hosseini, Seyed Moein ^{[2
]}

Moradi, Siyamak ^{[3
]}

Lee, Moonyong ^{[4
]}

Bahadori, Alireza ^{[5
]}

机构：

[1] Islamic Azad Univ, Ahvaz Branch, Young Researchers & Elite Club, Ahvaz, Iran

[2] Petr Univ Technol, Ahwaz Fac Petr Engn, Dept Petr Engn, Ahvaz, Iran

[3] Petr Univ Technol, Abadan Fac Petr Engn, Abadan, Iran

[4] Yeungnam Univ, Sch Chem Engn, Gyeungsan, South Korea

[5] Southern Cross Univ, Sch Environm Sci & Engn, POB 157, Lismore, NSW, Australia

来源：

PETROLEUM SCIENCE AND TECHNOLOGY | 2016年 / 34卷 / 23期

关键词：

Crude oil; oil production; permeability; modeling; flowing porosity; oil reservoir; OPTIMIZATION; PREDICTION;

D O I：

10.1080/10916466.2016.1233251

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

This work highlights the application of an adaptive neuro-fuzzy inference system (ANFIS) for predictions of NMR log parameters including free flowing porosity (FFP) and permeability by using field log data. The input parameters of model were neutron porosity, sonic transit time, bulk density, and electrical resistivity. The outputs of model were also permeability and FFP values. The ANFIS model was trained by using hybrid method. Results showed that the developed model is effective in prediction of field NMR log data. Outcomes of this study can be used in areas of petroleum engineering where accurate and immediate predictions of logging data are required.

引用

页码：1872 / 1879

页数：8

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