A Deep Learning-Accelerated Data Assimilation and Forecasting Workflow for Commercial-Scale Geologic Carbon Storage (2021-05-09T00:00:00.000000Z)

TL;DR

It is proposed to leverage physical understandings of porous medium flow behavior with deep learning techniques to develop a fast data assimilation-reservoir response forecasting workflow that can complete history matching and reservoir forecasting with uncertainty quantification in less than one hour on a mainstream personal workstation.

Authors

Hewei Tang

1 papers

P. Fu

1 papers

C. Sherman

1 papers

Jize Zhang

1 papers

X. Ju

1 papers

Franccois P. Hamon

1 papers

N. Azzolina

1 papers

Matthew E. Burton-Kelly

1 papers

J. Morris

1 papers

TL;DR

Authors

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