This paper presents a review of proper orthogonal decomposition (POD) methods for order
reduction in a variety of research areas. The historical development and basic mathematical …

Many aspects of reservoir management can be expected to benefit from the application of
computational optimization procedures. The focus of this review paper is on well control …

A quadratic approximation manifold is presented for performing nonlinear, projection-based,
model order reduction (PMOR). It constitutes a departure from the traditional affine subspace …

Deep learning (DL) is a numerical method that approximates functions. Recently, its use has
become attractive for the simulation and inversion of multiple problems in computational …

A new reduced-order model based on trajectory piecewise quadratic (TPWQ)
approximations and proper orthogonal decomposition (POD) is introduced and applied for …

In this work, we develop Non-Intrusive Reduced Order Models (NIROMs) that combine
Proper Orthogonal Decomposition (POD) with a Radial Basis Function (RBF) interpolation …

We present a global/local model reduction for fast multiscale reservoir simulations in highly
heterogeneous porous media. Our approach identifies a low-dimensional structure in the …

This paper presents a literature review on methods for enabling real-time analysis in digital
twins, which are virtual models of physical systems. The advantages of digital twins are …

Abstract The Capacitance Resistance Model (CRM) is a fast way for modeling and
simulating gas and waterflooding recovery processes, making it a useful tool for improving …

The objective of this paper is to introduce a novel paradigm to reduce the computational
effort in waterflooding global optimization problems while realizing smooth well control …