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Code for generating the analysis, plots, and manuscript for "Comparison of permeability predictions on cemented sandstones with physics-based and machine learning approaches"

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Permeability prediction for cemented sandstones

Code for generating the analysis, plots, and manuscript for "Comparison of permeability predictions on cemented sandstones with physics-based and machine learning approaches"

The RMD files for the data exploration are are garn-ML.Rmd and garn-panda.Rmd. The code to generate the paper is in permeability_prediction_in_sandstones. The styles reference file is styles-ref.docx.

You can read a preprint of the paper at EarthArXiV. The peer-accepted paper is in the Journal of Natural Gas Science and Engineering.

The Markdown version of the pre-print is at permeability_prediction_in_sandstones.Rmd.

To request the data that went into the paper, please email Frank Male.

You can cite the paper as:

Male, F., Jensen, J.L., Lake, L.W., 2020. Comparison of permeability predictions on cemented sandstones with physics-based and machine learning approaches. Journal of Natural Gas Science and Engineering. DOI: 10.1016/j.jngse.2020.103244

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Code for generating the analysis, plots, and manuscript for "Comparison of permeability predictions on cemented sandstones with physics-based and machine learning approaches"

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