4.5 Article

Estimating the initial pressure, permeability and skin factor of oil reservoirs using artificial neural networks

期刊

出版社

ELSEVIER
DOI: 10.1016/j.petrol.2005.09.002

关键词

artificial neural networks; initial pressure; permeability; skin factor; pressure build up test; well test

向作者/读者索取更多资源

Artificial neural network, a biologically inspired computing method which has an ability to learn, self-adjust, and be trained, provides a powerful tool in solving pattern recognition problems. In this study, a new approach based on artificial neural networks (ANNs) has been designed to estimate the initial pressure, permeability and skin factor of oil reservoir using the pressure build up test data. Five sets of actual field data in conventional and dual porosity reservoirs have been used to test the results of the neural network. The results from the network are in good agreement with the results from Homer plot. Finally, it is shown that the application of artificial neural networks in a pressure build up test reduces the cost of the test and it is also a valuable tool for well testing. (c) 2005 Elsevier B.V. All rights reserved,

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据