Stacked ensemble model for reservoir characterisation to predict log properties from seismic signals
Author:
Funder
Oil and Natural Gas Corporation
Publisher
Springer Science and Business Media LLC
Subject
Computational Mathematics,Computational Theory and Mathematics,Computers in Earth Sciences,Computer Science Applications
Link
https://link.springer.com/content/pdf/10.1007/s10596-023-10248-9.pdf
Reference34 articles.
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3. Mishra, S., Datta-Gupta, A.: Applied Statistical Modeling and Data Analytics: A Practical Guide for the Petroleum Geosciences. Elsevier (2017)
4. Bhattacharya, S., Mishra, S.: Applications of machine learning for facies and fracture prediction using bayesian network theory and random forest: Case studies from the Appalachian Basin, USA. J. Pet. Sci. Eng. 170, 1005–1017 (2018)
5. Sebtosheikh, M.A., Salehi, A.: Lithology prediction by support vector classifiers using inverted seismic attributes data and petrophysical logs as a new approach and investigation of training data set size effect on its performance in a heterogeneous carbonate reservoir. J. Pet. Sci. Eng. 134, 143–149 (2015)
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