On the feasibility of using physics-informed machine learning for underground reservoir pressure management

2021 ◽  
pp. 115006
Author(s):  
Dylan Robert Harp ◽  
Dan O’Malley ◽  
Bicheng Yan ◽  
Rajesh Pawar
2014 ◽  
Author(s):  
R. Srinivas Prasad ◽  
Fulbert Crisologo Del Mundo ◽  
Michael Lev Litvak ◽  
James John Flynn ◽  
Stephen T. Edwards

2022 ◽  
Vol 114 ◽  
pp. 103559
Author(s):  
Marius Dewar ◽  
Jerry Blackford ◽  
Tony Espie ◽  
Sarah Wilford ◽  
Nicolas Bouffin

2020 ◽  
Vol 43 ◽  
Author(s):  
Myrthe Faber

Abstract Gilead et al. state that abstraction supports mental travel, and that mental travel critically relies on abstraction. I propose an important addition to this theoretical framework, namely that mental travel might also support abstraction. Specifically, I argue that spontaneous mental travel (mind wandering), much like data augmentation in machine learning, provides variability in mental content and context necessary for abstraction.


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