Robust quantification of parametric uncertainty for surfactant-polymer flooding

DOI10.1007/s10596-013-9384-9zbMath1393.86007OpenAlexW1988921875MaRDI QIDQ1663636

Y. Aharonov

Publication date: 22 August 2018

Published in: Computational Geosciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10596-013-9384-9

zbMATH Keywords

Monte Carlo simulationpolynomial chaosenhanced oil recoveryprobabilistic collocation method

Mathematics Subject Classification ID

Monte Carlo methods (65C05) Hydrology, hydrography, oceanography (86A05) Flows in porous media; filtration; seepage (76S05) Computational methods for problems pertaining to geophysics (86-08)

Related Items (1)

Robust optimization of subsurface flow using polynomial chaos and response surface surrogates

Uses Software

• ORTHPOL

Cites Work

• The multi-element probabilistic collocation method (ME-PCM): Error analysis and applications
• Probabilistic collocation used in a Two-Step approached for efficient uncertainty quantification in computational fluid dynamics
• A Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data
• Algorithm 726: ORTHPOL–a package of routines for generating orthogonal polynomials and Gauss-type quadrature rules
• The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations
• High-Order Collocation Methods for Differential Equations with Random Inputs
• Calculation of Gauss Quadrature Rules
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