Real-time high-resolution CO<sub>2</sub> geological storage prediction using nested Fourier neural operators-Reference-Cited by-同舟云学术

Real-time high-resolution CO₂ geological storage prediction using nested Fourier neural operators

Published:2023 Issue:4 Volume:16 Page:1732-1741
ISSN:1754-5692
Container-title:Energy & Environmental Science
language:en
Short-container-title:Energy Environ. Sci.

Author:

Wen Gege¹^ORCID,Li Zongyi²,Long Qirui¹^ORCID,Azizzadenesheli Kamyar³,Anandkumar Anima²³,Benson Sally M.¹

Affiliation:

1. Energy Sciences and Engineering, Stanford University, Stanford, 94305, CA, USA

2. Computing and Mathematical Sciences, California Institute of Technology, Pasadena, 91125, CA, USA

3. NVIDIA Corporation, Santa Clara, 95051, CA, USA

Abstract

Nested FNO is a machine learning framework that offers a general-purpose numerical simulator alternative to provide high-resolution CO2 storage predictions in real time.

Publisher

Royal Society of Chemistry (RSC)

Subject

Pollution,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment,Environmental Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2023/EE/D2EE04204E

Reference76 articles.

1. IEA, Exploring Clean Energy Pathways: The Role of CO 2 Storage, IEA technical report, 2019

2. Residual fossil CO2 emissions in 1.5–2 °C pathways

3. The meaning of net zero and how to get it right

4. The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview

5. L.Cozzi , T.Gould , S.Bouckart , D.Crow , T.Kim , C.Mcglade , P.Olejarnik , B.Wanner and D.Wetzel , World Energy Outlook 2020, IEA technical report, 2020

Cited by 36 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Data-driven methods for flow and transport in porous media: A review;International Journal of Heat and Mass Transfer;2024-12

2. U-DeepONet: U-Net enhanced deep operator network for geologic carbon sequestration;Scientific Reports;2024-09-12

3. Synthetic ground motions in heterogeneous geologies from various sources: the HEMEW^S-3D database;Earth System Science Data;2024-09-03

4. An improved neural operator framework for large-scale CO2 storage operations;Geoenergy Science and Engineering;2024-09

5. Learning CO2 plume migration in faulted reservoirs with Graph Neural Networks;Computers & Geosciences;2024-09