Artificial Neural Network Modeling Enhancing Shear Wave Transit Time Prediction

被引：0

作者：

Mohammad Nabaei ^{[1
]}

Arash Shadravan ^{[1
]}

Khalil Shahbazi ^{[2
]}

机构：

[1] Islamic Azad University of Omidieh(YRC),No.8,Kargar St.Abadeh

[2] Petroleum,University of Technology

来源：

地学前缘 | 2009年 / S1期

关键词：

sonic velocity; geomechnical modeling; Artificial Neural Networks;

D O I：

暂无

中图分类号：

P618.13 [石油、天然气];

学科分类号：

0709 ; 081803 ;

摘要：

Sonic log is the most versatile reservoir evaluation tool that has been introduced to the industry. Compaction,erosion and over pressurized zone can be evaluated by sonic log.Also primary porosity can be determined from compressional sonic wave transit time and secondary porosity will be calculated by comparing sonic derived porosity log with neutron and density based porosity log.On the other hand all of the rock mechanical properties can be evaluated using simultaneous use of compressional and shear sonic wave transit time.It is essential to have shear

引用

页码：85 / 85

页数：1