Application of Evolutionary Neural Networks for Well-logging Recognition in Petroleum Reservoir
Document Type
Conference Presentation
Department
Computer Science
Conference Title
Seventh International Conference on Computational Intelligence and Security
Location
Hainan, China
Conference Dates
December 3-4, 2011
Date of Presentation
12-3-2011
Abstract
A critical task of well-logging interpretation is to differentiate oil-gas-water layers. Other approaches based on data exploration and low recognition rate are difficult to generalize oil-gas-water layers identification because of the high moisture content in the later period of development. In this research we utilize evolutionary neural networks to build the interpreting model of oil-gas-water layers and extracting well-logging parameters. By using an evolutionary neural network method to recognize reservoir stratum, it can efficiently distinguish oil-gas-water layers.
First Page
362
Last Page
366
DOI
10.1109/CIS.2011.87
Recommended Citation
Zhu, K.,
Song, H.,
Gao, J.,
&
Cheng, G.
(2011).
Application of Evolutionary Neural Networks for Well-logging Recognition in Petroleum Reservoir.
Paper presented at Seventh International Conference on Computational Intelligence and Security in Hainan, China.
https://scholarlycommons.pacific.edu/soecs-facpres/96
