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- W2364258368 abstract "This text makes a study of parameter(porosity、permeability) of container rock using the principle of the of Radial Basis Function(RBF) neural networks ,taking good log data and data of core testing as study samples of networks model, passing the study of the networks and training, building up RBF neural networks model of well logging interpretation . we calculate porosity and permeability of clastic reservoir rocks of many wells at HangJingQi area in the ordos basin . Being compared with the traditional statistic methods, neural network method displays the better accuracy and stronger practicability." @default.
- W2364258368 created "2016-06-24" @default.
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- W2364258368 date "2005-01-01" @default.
- W2364258368 modified "2023-09-25" @default.
- W2364258368 title "UTILIZING NEURAL NETWORKS TO PREDICT POROSITY AND PERMEABILITY" @default.
- W2364258368 hasPublicationYear "2005" @default.
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