The generalized polynomial chaos method with multiwavelet basis functions is applied to
the Buckley–Leverett equation. We consider a spatially homogeneous domain modeled as a …

We present a Parametrization of the Physics Informed Neural Network (P-PINN) approach to
tackle the problem of uncertainty quantification in reservoir engineering problems. We …

We present a Parametrization of the Physics Informed Neural Network (P-PINN) approach to
tackle the problem of uncertainty quantification in reservoir engineering problems. We …

A stochastic Galerkin formulation for the transport of CO _2 CO 2 in a tilted aquifer with
uncertain heterogeneous properties is presented. We consider a simplified physics model …

We develop a probabilistic approach to map parametric uncertainty to output state
uncertainty in first‐order hyperbolic conservation laws. We analyze this problem for …

We analyze the problem of uncertainty propagation for nonlinear two-phase transport in
heterogeneous porous media. Specifically, we study the evolution of the saturation field …

Elucidating multiscale, multiphase and multiphysics phenomena of flow and transport
processes in porous media is the cornerstone of numerous environmental and engineering …

Because geophysical data are inexorably sparse and incomplete, stochastic treatments of
simulated responses are crucial to explore possible scenarios and assess risks in …

Oil recovery forecast relies on predictions of saturation fields from reservoir simulations.
These predictions, in return, are dependent on the quality of the input data available, such …