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- W145223902 abstract "This study focuses on reservoir parameter estimation using extreme learning machine in heterogeneous sandstone reservoir. The specific aim of work is to obtain accurate porosity and permeability which has proven to be difficult by conventional petrophysical methods in wells without core data. 4950 samples of 15 wells with core data have been used to train the neural network, and robust ELM algorithm provides fast and accurate prediction results. The network model is then applied to estimate porosity and permeability for the remaining wells. Based on the predicted results, reservoir parameter distribution character has been analyzed. Potential zone has been proposed for further research in the survey." @default.
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- W145223902 date "2015-01-01" @default.
- W145223902 modified "2023-10-17" @default.
- W145223902 title "Extreme Learning Machine for Reservoir Parameter Estimation in Heterogeneous Reservoir" @default.
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- W145223902 doi "https://doi.org/10.1007/978-3-319-14066-7_20" @default.
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