Based on RBF Neural Network Modeling of Well Test System

Jia Tian

doi:10.4028/www.scientific.net/AMM.535.606

Paper Titles

Simulation Analysis of an Ambulance Carriage Interior Noise
p.581

Study on Application of Urban Underground Drain Pipeline Information Modeling as an Auxiliary Decision Support in Urban Planning
p.586

A Modified Model for Friction Reduction by Vibrating Drill-String Longitudinally
p.597

Application Prospects in China of Oil Shale In Situ Mining Method and an Improved Method
p.602

Based on RBF Neural Network Modeling of Well Test System
p.606

Research on Dynamic Mechanism of Green Coal Mine Construction
p.610

Research on Gas Content Prediction Model of Hebi No.6 Mine Based on Quantification Theory
p.614

Study on Coalbed Methane well Type Optimization of Badaowan Formation in Junggar Basin
p.622

The Analysis of the Coal Floor Water Inrush Effected by the Fault
p.626

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 535Based on RBF Neural Network Modeling of Well Test...

Based on RBF Neural Network Modeling of Well Test System

Abstract:

The Neural Network Toolbox in MATLAB is a powerful instrument of analyzing and designing a neural network system. RBF Neural Network has small computational burden and fast learning rate and is not liable to be trapped by local minimal points etc. So it is an effective means to identify and model a system. In this paper, the Neural Network Toolbox in MATLAB and RBF Neural Network are combined to solve the problem of modeling the pressure in oilfield test well systems and the result is excellent.

You might also be interested in these eBooks

Energy Engineering and Environment Engineering

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volume 535)

Pages:

606-609

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.535.606

Citation:

Cite this paper

Online since:

February 2014

Authors:

Jia Tian

Keywords:

MATLAB, RBF Neural Network, Test Well Systems

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Liu Jie modern well test interpretation in oilfield development application [J]. Glamor China, 2009, 20: 29.

Google Scholar

[2] Zhao Yulong, Zhang Liehui, Green wins Portland. Triple medium non-Newtonian power law fluid reservoir model and typical curve of well test analysis [J]. Hydrodynamics Research and Development Series A, 2010, 02: 254-261.

Google Scholar

[3] WangHaijun, LiYanman, SongYan, LiChangjie. Dry low permeability oilfield well testing technology security research and practice [A]. Jilin Science and Technology Association. Low-carbon economy and scientific development - Science and Technology of Jilin Province sixth Annual Conference Proceedings [C]. Jilin Science and Technology Association:, 2010: 3.

DOI: 10.3923/itj.2013.462.465

Google Scholar