327 citations · 984 across the 23 of their papers we have counts for
5 papers · 1 filter
Quantum Algorithms for Geologic Fracture Networks
Jessie M. Henderson, Marianna Podzorova, M. Cerezo +4
Solving large systems of equations is a challenge for modeling natural phenomena, such as simulating subsurface flow. To avoid systems that are intractable on current computers, it…
Predictive Scale-Bridging Simulations through Active Learning
Satish Karra, Mohamed Mehana, Nicholas Lubbers +12
Throughout computational science, there is a growing need to utilize the continual improvements in raw computational horsepower to achieve greater physical fidelity through scale-b…
Physics-informed machine learning with differentiable programming for heterogeneous underground reservoir pressure management
Aleksandra Pachalieva, Daniel O'Malley, Dylan Robert Harp +1
Avoiding over-pressurization in subsurface reservoirs is critical for applications like CO2 sequestration and wastewater injection. Managing the pressures by controlling injection/…
Quantum Computing and Preconditioners for Hydrological Linear Systems
John Golden, Daniel O'Malley, Hari Viswanathan
Modeling hydrological fracture networks is a hallmark challenge in computational earth sciences. Accurately predicting critical features of fracture systems, e.g. percolation, can…
Machine Learning in Heterogeneous Porous Materials
Marta D'Elia, Hang Deng, Cedric Fraces +21
The "Workshop on Machine learning in heterogeneous porous materials" brought together international scientific communities of applied mathematics, porous media, and material scienc…