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- W2034503860 abstract "Abstract A key parameter for reservoir characterization is permeability distribution. Most well log data and core permeability values are corrupted by noise (such as uncertain depth-matching, core testing conditions, and thin beddings). In this work, the authors first used wavelet as a new powerful tool for de-noising data points and then they investigated how the integration of back propagation with group based symbiotic evolution improves the reliability and prediction capability of neuro-fuzzy systems for predicting permeability of real reservoir data. Keywords: back propagationgenetic algorithmgroup based symbiotic evolutionneural networkpermeability estimationreservoirwavelet" @default.
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- W2034503860 date "2013-06-01" @default.
- W2034503860 modified "2023-10-17" @default.
- W2034503860 title "A Hybrid Symbiotic Evolution–Neuro Fuzzy Strategy for Permeability Estimation of the Reservoir" @default.
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- W2034503860 doi "https://doi.org/10.1080/10916466.2010.538790" @default.
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