7 papers
Machine learning enhanced data assimilation framework for multiscale carbonate rock characterization
Zhenkai Bo, Ahmed H. Elsheikh, Hannah P. Menke +5
Carbonate reservoirs offer significant capacity for subsurface carbon storage, oil production, and underground hydrogen storage. X-ray computed tomography (X-ray CT) coupled with n…
A Benchmark Dataset for Machine Learning Surrogates of Pore-Scale CO2-Water Interaction
Alhasan Abdellatif, Hannah P. Menke, Julien Maes +2
Accurately capturing the complex interaction between CO2 and water in porous media at the pore scale is essential for various geoscience applications, including carbon capture and…
A Deep-Learning Iterative Stacked Approach for Prediction of Reactive Dissolution in Porous Media
Marcos Cirne, Hannah Menke, Alhasan Abdellatif +3
Simulating reactive dissolution of solid minerals in porous media has many subsurface applications, including carbon capture and storage (CCS), geothermal systems and oil & gas rec…
Scalable CFD Simulations in Multi-Billion Voxel Micro-CT Images of Porous Materials Using OpenFOAM on ARCHER2
J. Maes, Gavin J. Pringle, Hannah P. Menke
This study investigates the use of High-Performance Computing (HPC) to simulate flow and transport in ultra-large micro-CT images of porous materials using Computational Fluid Dyna…
Inference of microporosity phase properties in heterogeneous carbonate rock with data assimilation techniques
Zhenkai Bo, Ahmed H. Elsheikh, Hannah P. Menke +3
Accurate digital rock modeling of carbonate rocks is limited by the difficulty in acquiring morphological information on small-scale pore structures. Defined as microporosity phase…
When Cubic Law and Darcy Fail: Bayesian Correction of Model Misspecification in Fracture Conductivities
Sarah Perez, Florian Doster, Julien Maes +3
Structural uncertainties and unresolved features in fault zones hinder the assessment of leakage risks in subsurface CO2 storage. Understanding multi-scale uncertainties in fractur…