Funder
Department of Energy
Stanford Smart Fields Consortium
Stanford Center for Carbon Storage
Publisher
Springer Science and Business Media LLC
Subject
Computational Mathematics,Computational Theory and Mathematics,Computers in Earth Sciences,Computer Science Applications
Reference27 articles.
1. Ayani, M., Grana, D., Liu, M.: Stochastic inversion method of time-lapse controlled source electromagnetic data for CO$$_2$$ plume monitoring. Int. J. Greenhouse Gas Control 100, 103098 (2020)
2. Barros, E., Leeuwenburgh, O., Szklarz, S.: Quantitative assessment of monitoring strategies for conformance verification of CO$$_2$$ storage projects. Int. J. Greenhouse Gas Control 110, 103403 (2021)
3. Cameron, D.A., Durlofsky, L.J.: Optimization and data assimilation for geological carbon storage. Computational models for CO$$_2$$ sequestration and compressed air energy storage, R. Al-Khoury and J. Bundschuh, eds., Taylor & Francis Group/CRC Press pp. 357–388 (2014)
4. Cameron, D.A., Durlofsky, L.J., Benson, S.M.: Use of above-zone pressure data to locate and quantify leaks during carbon storage operations. Int. J. Greenhouse Gas Control 52, 32–43 (2016)
5. Chen, B., Harp, D.R., Lin, Y., Keating, E.H., Pawar, R.J.: Geologic CO$$_2$$ sequestration monitoring design: a machine learning and uncertainty quantification based approach. Appl. Energy 225, 332–345 (2018)
Cited by
2 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