Capacitance resistance models (CRMs) comprise a family of material balance reservoir
models that have been applied to primary, secondary and tertiary recovery processes …

Abstract Underground hydrogen (H 2) storage (UHS) has emerged as a promising
technology to facilitate the widespread adoption of fluctuating renewable energy sources …

A deep-learning-based surrogate model is developed and applied for predicting dynamic
subsurface flow in channelized geological models. The surrogate model is based on deep …

Traditional linear subspace reduced order models (LS-ROMs) are able to accelerate
physical simulations in which the intrinsic solution space falls into a subspace with a small …

A new deep-learning-based reduced-order modeling (ROM) framework is proposed for
application in subsurface flow simulation. The reduced-order model is based on an existing …

In the petroleum industry, artificial intelligence has been applied in seismic and logging
interpretation, accurate modeling, optimized drilling operations, well dynamics prediction …

As a mathematical model of high-speed flow and shock wave propagation in a complex
multimaterial setting, Lagrangian hydrodynamics is characterized by moving meshes …

Lattice-type structures can provide a combination of stiffness with light weight that is
desirable in a variety of applications. Design optimization of these structures must rely on …

While projection-based reduced order models can reduce the dimension of full order
solutions, the resulting reduced models may still contain terms that scale with the full order …

Abstract The Rayleigh-Taylor instability is a classical hydrodynamic instability of great
interest in various disciplines of science and engineering, including astrophysics …