Dr. Atul Kumar Patidar

University of Petroleum and Energy Studies (UPES) - Department of Petroleum Engineering and Earth Sciences

Dehradun

India

SCHOLARLY PAPERS

2

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Scholarly Papers (2)

1.

Prediction of Sonic Log and Correlation of Lithology by Comparing Geophysical Well Log Data Using Machine Learning Principles

Geojournal (2021) https://doi.org/10.1007/s10708-021-10502-6
Posted: 14 Dec 2021
University of Petroleum and Energy Studies (UPES) - Department of Petroleum Engineering and Earth Sciences, University of Petroleum and Energy Studies (UPES) - Department of Petroleum Engineering and Earth Sciences, University of Petroleum and Energy Studies (UPES) - Department of Petroleum Engineering and Earth Sciences, University of Petroleum and Energy Studies (UPES) - Department of Petroleum Engineering and Earth Sciences, University of Petroleum and Energy Studies (UPES) - Department of Petroleum Engineering and Earth Sciences, University of Petroleum and Energy Studies (UPES) - Department of Petroleum Engineering and Earth Sciences, University of Petroleum and Energy Studies (UPES) and University of Petroleum and Energy Studies (UPES)

Abstract:

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keywords well log, sonic log, k-meansclustering, regression analysis, neural network, machine learning (ML), silhouette score, CH score, root mean squared error (RMSE), R2scores

2.

Contrasting Machine Learning Regression Algorithms Used for the Estimation of Permeability from Well Log Data

Arabian Journal of Geosciences (2021) 14: 2070; https://doi.org/10.1007/s12517-021-08390-8
Posted: 10 Dec 2021
Narman Khilrani, Piysuh Prajapati and Dr. Atul Kumar Patidar
University of Petroleum and Energy Studies (UPES) - Department of Petroleum Engineering and Earth Sciences, University of Petroleum and Energy Studies (UPES) - Department of Petroleum Engineering and Earth Sciences and University of Petroleum and Energy Studies (UPES) - Department of Petroleum Engineering and Earth Sciences

Abstract:

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keywords machine learning, Klinkenberg core corrected permeability, regression, core data, R2 score