| 贝叶斯正规化算法在油藏参数拟合方面的应用 |
| |
| 引用本文： | 潘永才,单文兵,张尚辉,王富.贝叶斯正规化算法在油藏参数拟合方面的应用[J].物联网技术,2012(4):45-47. |
| |
| 作者姓名： | 潘永才 单文兵 张尚辉 王富 |
| |
| 作者单位： | 湖北大学物电学院 |
| |
| 摘 要： | 通过已知测井资料对油藏储量进行预测,是目前石油行业一个重要的研究课题。文章介绍了一种基于贝叶斯正规化算法的BP神经网络,并把网络应用到油藏参数拟合过程中的具体方法,该方法对提高石油生产效率、降低成本具有很大的作用。
|
| 关 键 词： | 油藏 拟合 贝叶斯 正规化算法 神经网络 |
Application of Bayesian regularization algorithm in reservoir parameter fitting |
| |
| PAN Yong-cai, SHAN Wen-bing, ZHANG Shang-hui, WANG Fu.Application of Bayesian regularization algorithm in reservoir parameter fitting[J].Internet of things technologies,2012(4):45-47. |
| |
| Authors: | PAN Yong-cai SHAN Wen-bing ZHANG Shang-hui WANG Fu |
| |
| Affiliation: | (Hubei University of things electrical College, Wuhan 430062, China) |
| |
| Abstract: | The known logging data to predict reservoir reserves is an important research topic in the oil industry. In this paper, the algorithm based on Bayesian regularization BP neural network is introduced and the applications to specific methods in the reservoir parameter fitting process is also described. This method plays a significant role in improving the oil production efficiency and reducing the costs. |
| |
| Keywords: | reservoir fitting Bayesian regularization algorithm neural network |
| 本文献已被 CNKI 等数据库收录！ |
