1 citations · 1 across the 5 of their papers we have counts for
8 papers
Surrogate models for Rock-Fluid Interaction: A Grid-Size-Invariant Approach
Nathalie C. Pinheiro, Donghu Guo, Hannah P. Menke +4
Modelling rock-fluid interaction requires solving a set of partial differential equations (PDEs) to predict the flow behaviour and the reactions of the fluid with the rock on the i…
Probabilistic Upscaling of Hydrodynamics in Geological Fractures Under Uncertainty
Sarah Perez, Florian Doster, Hannah Menke +2
Flow and transport in fractured geological media are strongly controlled by aperture heterogeneity and uncertainty in subsurface characterisation, yet most upscaling approaches rel…
Machine learning for sustainable geoenergy: uncertainty, physics and decision-ready inference
Hannah P. Menke, Ahmed H. Elsheikh, Lingli Wei +2
Geoenergy projects (CO2 storage, geothermal, subsurface H2 generation/storage, critical minerals from subsurface fluids, or nuclear waste disposal) increasingly follow a petroleum-…
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…
Feature-Modulated UFNO for Improved Prediction of Multiphase Flow in Porous Media
Alhasan Abdellatif, Hannah P. Menke, Florian Doster +2
The UNet-enhanced Fourier Neural Operator (UFNO) extends the Fourier Neural Operator (FNO) by incorporating a parallel UNet pathway, enabling the retention of both high- and low-fr…
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…