模糊集合论和神经网络在油井测试中的应用方法研究  

Application of Fuzzy Sets Theory and Artificial Neural Networks in Well Measurement Based on

作　　者：吴新杰[1] 闫光辉[1] 刘艳侠[1] 梁雅秋[1] 

机构地区：[1]辽宁大学物理系,辽宁沈阳110036

出　　处：《辽宁大学学报（自然科学版）》2000年第2期131-134,共4页Journal of Liaoning University：Natural Sciences Edition

摘　　要：提出了一种基于模糊集合论和人工神经网络处理油井测量问题的方法 .首先利用模糊集合论中的模糊聚类方法 ,将所使用的各种传感器根据灵敏度特性曲线进行分档归类 ,然后利用人工神经网络对各档次的传感器进行非线性估计 ,并在此基础上形成了一套完整的算法 ,对于油井测试中测量精度的提高具有一定的实用意义 .A method dealing with wells measurement has been presented by using fuzzy sets theory and artificial neural networks. Firstly, based on fuzzy sets theory, various sensors were classified according to their sensitivity curves. Secondly, by using artificial neural networks, for nonlinear estimation for was proposed. With this method, a simple and practical algorithm has been developed, which can promote the precision of well measurement.

关 键 词：模糊聚类 神经网络 模糊集合论 油井测试 应用 

分 类 号：TE15[石油与天然气工程—油气勘探] TP18[自动化与计算机技术—控制理论与控制工程]