Synergistic enhancement of productivity prediction using machine learning and integrated data from six shale basins of the USA

Author:

Kim SungilORCID,Kim Kwang Hyun,Lim Jung-Tek

Funder

Ministry of Trade, Industry and Energy

Korea Institute of Geoscience and Mineral Resources

Publisher

Elsevier BV

Reference72 articles.

1. Molecular characterization of kerogen and its implications for determining hydrocarbon potential, organic matter sources and thermal maturity in Marcellus Shale;Agrawal;Fuel,2018

2. Production Performance Estimation from Stimulation and Completion Parameters Using Machine Learning Approach in the Marcellus Shale;Al-Alwani,2019

3. Effect of basement tectonics on hydrocarbon generation, migration, and accumulation in northern Iraq;Ameen;AAPG Bull.,1992

4. Brine migrations across North America—the plate tectonics of groundwater;Bethke;Annu. Rev. Earth Planet Sci.,1990

5. New horizon in energy: shale gas;Bilgen;J. Nat. Gas Sci. Eng.,2016

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