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Uncertainty Quantification of Fluid Leakage and Fault Instability in Geologic CO2 Storage

Autor: Lu, Hannah, Salo-Salgado, Lluis, Marzouk, Youssef M., Juanes, Ruben

Geologic CO$_2$ storage is an important strategy for reducing greenhouse gas emissions to the atmosphere and mitigating climate change. In this process, coupling between mechanical deformation and fluid flow in fault zones is a key determinant of fau

Externí odkaz: http://arxiv.org/abs/2411.08039

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An uncertainty-aware Digital Shadow for underground multimodal CO2 storage monitoring

Autor: Gahlot, Abhinav Prakash, Orozco, Rafael, Yin, Ziyi, Herrmann, Felix J.

Geological Carbon Storage GCS is arguably the only scalable net-negative CO2 emission technology available While promising subsurface complexities and heterogeneity of reservoir properties demand a systematic approach to quantify uncertainty when opt

Externí odkaz: http://arxiv.org/abs/2410.01218

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Graph Network Surrogate Model for Optimizing the Placement of Horizontal Injection Wells for CO2 Storage

Autor: Tang, Haoyu, Durlofsky, Louis J.

Optimizing the locations of multiple CO2 injection wells will be essential as we proceed from demonstration-scale to large-scale carbon storage operations. Well placement optimization is, however, a computationally intensive task because the flow res

Externí odkaz: http://arxiv.org/abs/2410.07142

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Accelerated training of deep learning surrogate models for surface displacement and flow, with application to MCMC-based history matching of CO2 storage operations

Autor: Han, Yifu, Hamon, Francois P., Durlofsky, Louis J.

Deep learning surrogate modeling shows great promise for subsurface flow applications, but the training demands can be substantial. Here we introduce a new surrogate modeling framework to predict CO2 saturation, pressure and surface displacement for

Externí odkaz: http://arxiv.org/abs/2408.10717

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Deep Learning Framework for History Matching CO2 Storage with 4D Seismic and Monitoring Well Data

Autor: Wang, Nanzhe, Durlofsky, Louis J.

Geological carbon storage entails the injection of megatonnes of supercritical CO2 into subsurface formations. The properties of these formations are usually highly uncertain, which makes design and optimization of large-scale storage operations chal

Externí odkaz: http://arxiv.org/abs/2408.01575

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