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Deep learning inversion of gravity data for detection of CO2 plumes in overlying aquifers

  • Published:2022-01 Issue: Volume:196 Page:104507
  • ISSN:0926-9851
  • Container-title:Journal of Applied Geophysics
  • language:en
  • Short-container-title:Journal of Applied Geophysics

Author:

Yang Xianjin,Chen Xiao,Smith Megan M.

Funder

Office of Fossil Energy

Lawrence Livermore National Laboratory

U.S. Department of Energy

National Energy Technology Laboratory

Publisher

Elsevier BV

Subject

Geophysics

Reference50 articles.

1. A review of CO 2 storage in geological formations emphasizing modeling, monitoring and capacity estimation approaches;Ajayi;Pet. Sci.,2019

2. Monitoring gas production and CO2 injection at the Sleipner field using time-lapse gravimetry;Alnes;Geophysics,2008

3. Time-lapse gravity monitoring of CO2 migration based on numerical modeling of a faulted storage complex;Appriou;Int. J. Greenh Gas Con.,2020

4. Deep-learning tomography;Araya-Polo;Lead. Edge,2018

5. Risk-based post injection site care and monitoring for commercial-scale carbon storage: Reevaluation of the FutureGen 2.0 site using NRAP-Open-IAM and DREAM;Bacon;Int. J. Greenh Gas Con.,2019
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