Paper Title:
Application of Probabilistic Neural Network Technique in Identifying Low Porosity and Low Permeability Gas-Layers in Logging Data
  Abstract

In view of poor Physical Properties,complex Pore Structure and high saturation of low porosity and low permeability gas layers ,in order to overcome the difficult of fluid property identification in low porosity and low permeability gas layers using conventional method, probabilistic neural network technique was Proposed.According to an example for low porosity and low permeability gas reservoil in Southwest China, Combined with well testing data,logging Response Characteristics of various fluid property layers were analyzed.According the correlation between logging Response Characteristic values and fluid property, PNN was trained and PNN prediction model was established. fluid property in the region layers were identified.The results showed that the PNN prediction model was very promising influid property identification.

  Info
Periodical
Edited by
Qi Luo
Pages
1712-1715
DOI
10.4028/www.scientific.net/AMM.58-60.1712
Citation
C. Zhang, G. C. Pan, "Application of Probabilistic Neural Network Technique in Identifying Low Porosity and Low Permeability Gas-Layers in Logging Data", Applied Mechanics and Materials, Vols. 58-60, pp. 1712-1715, 2011
Online since
June 2011
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