Machine learning inversion of time-lapse three-axis borehole gravity data for CO2 monitoring
Author:
Affiliation:
1. Colorado School of Mines
Publisher
Society of Exploration Geophysicists and American Association of Petroleum Geologists
Link
https://library.seg.org/doi/pdf/10.1190/image2022-3745388.1
Reference20 articles.
1. Solving ill-posed inverse problems using iterative deep neural networks
2. Simultaneous CO2 injection and water production to optimise aquifer storage capacity
3. Time-lapse gravity monitoring: A systematic 4D approach with application to aquifer storage and recovery
4. Simulation of industrial-scale CO2 storage: Multi-scale heterogeneity and its impacts on storage capacity, injectivity and leakage
5. Evaluating time-lapse borehole gravity for CO2 plume detection at SECARB Cranfield
Cited by 4 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. A Test-Time Learning Approach to Reparameterize the Geophysical Inverse Problem With a Convolutional Neural Network;IEEE Transactions on Geoscience and Remote Sensing;2024
2. Three‐axis borehole gravity monitoring for CO2 storage using machine learning coupled to fluid flow simulator;Geophysical Prospecting;2023-09-08
3. Surface Gravity Response of CO2 Storage in the Johansen Deep Reservoir;IEEE Transactions on Geoscience and Remote Sensing;2023
4. Inversion of Time-Lapse Surface Gravity Data for Detection of 3-D CO2 Plumes via Deep Learning;IEEE Transactions on Geoscience and Remote Sensing;2023
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