Porosity Prediction from Well Logs Using Back Propagation Neural Network Optimized by Genetic Algorithm in One Heterogeneous Oil Reservoirs of Ordos Basin, China

A reliable and effective model for reservoir physical property prediction is a key to reservoir characterization and management. At present, using well logging data to estimate reservoir physical parameters is an important means for reservoir evaluation. Based on the characteristics of large quantit...

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Veröffentlicht in:	Journal of earth science (Wuhan, China) China), 2021-08, Vol.32 (4), p.828-838
Hauptverfasser:	Chen, Lin, Lin, Weibing, Chen, Ping, Jiang, Shu, Liu, Lu, Hu, Haiyan
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial neural networks Back propagation Back propagation networks Biogeosciences Data logging Earth and Environmental Science Earth Sciences Gamma rays Genetic algorithms Geochemistry Geology Geotechnical Engineering & Applied Earth Sciences Logging Neural networks Neurons Oil reservoirs Optimization Parameter estimation Parameters Physical properties Porosity Predictions Propagation Regression models Reservoirs Sandstone Sedimentary rocks Well logging Well logs
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