Advertisement

Neural Network Based Modeling for Oil Well Pressure Data Compensation System

  • Jian-long Tang
  • En li
  • Zeng-guang Hou
  • Qi Zuo
  • Zi-ze Liang
  • Min Tan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4114)

Abstract

This paper mainly focuses on the modeling of oil well pressure data compensation system(OWPCS) based on Neural Networks(NN). Firstly, the operational principle and configuration of OWPCS is described. Then the currently widely used modeling method for OWPCS is given, and its limitations and disadvantages are also illustrated. Secondly, in order to solve the OWPCS modeling problem more reasonably, a new approach based on Neural Network is proposed. Thirdly, the feasibility of using NN to solve this problem is analyzed, and a three-layer BP network is constructed to testify the new modeling method. Fourthly, considering the defect of BP learning algorithm and the special application environment of OWPCS, some improvements are given. Finally, experiment results are presented to show the reasonableness and effectiveness of the new method.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jian-long Tang
    • 1
  • En li
    • 1
  • Zeng-guang Hou
    • 1
  • Qi Zuo
    • 2
  • Zi-ze Liang
    • 1
  • Min Tan
    • 1
  1. 1.Laboratory of Complex System and Intelligence Science, Institute of Automation, Chinese Academy of Science , No.95 Zhongguancun. Road, BeijingChina
  2. 2.Automation Department Field Bus Tech&Automation Key lab. North China University of Technology, No.5 Jinyuanzhuang Road, Shijingshan District, BeijingChina

Personalised recommendations