Ensemble level upscaling for compositional flow simulation

DOI10.1007/s10596-015-9503-xzbMath1392.86013OpenAlexW572267005MaRDI QIDQ722834

Louis J. Durlofsky, Hangyu Li

Publication date: 27 July 2018

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

Full work available at URL: https://doi.org/10.1007/s10596-015-9503-x

zbMATH Keywords

simulationreservoir managementuncertainty quantificationcompositional flownear-well upscaling

Mathematics Subject Classification ID

Geostatistics (86A32) Computational methods for problems pertaining to geophysics (86-08) Geological problems (86A60)

Related Items (3)

Multifidelity framework for uncertainty quantification with multiple quantities of interest ⋮ Deep-learning-based upscaling method for geologic models via theory-guided convolutional neural network ⋮ Machine-learning-based modeling of coarse-scale error, with application to uncertainty quantification

Uses Software

• GSLIB
• SGeMS

Cites Work

• A coarse-scale compositional model
• Nonlinear two-point flux approximation for modeling full-tensor effects in subsurface flow simulations
• Coarse scale models of two-phase flow in heterogeneous reservoirs: Volume averaged equations and their relationship to existing upscaling techniques
• A comparison of two-phase dynamic upscaling methods based on fluid potentials
• Global variable compact multipoint methods for accurate upscaling with full-tensor effects
• Statistical assignment of upscaled flow functions for an ensemble of geological models
• Uncertainty Quantification for Subsurface Flow Problems Using Coarse-Scale Models
• Efficient Incorporation of Global Effects in Upscaled Models of Two-Phase Flow and Transport in Heterogeneous Formations
• Local-Global Two-Phase Upscaling of Flow and Transport in Heterogeneous Formations

This page was built for publication: Ensemble level upscaling for compositional flow simulation