A prefetching technique for prediction of porous media flows

DOI10.1007/s10596-014-9413-3zbMath1392.76081OpenAlexW1999807979MaRDI QIDQ723181

D. Kharzeev

Publication date: 30 July 2018

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

Full work available at URL: https://doi.org/10.1007/s10596-014-9413-3

zbMATH Keywords

porositypermeabilitylikelihood functionMarkov Chain Monte Carlouncertainty quantificationpre-fetching

Mathematics Subject Classification ID

Monte Carlo methods (65C05) Fluid-solid interactions (including aero- and hydro-elasticity, porosity, etc.) (74F10) Flows in porous media; filtration; seepage (76S05) Numerical analysis or methods applied to Markov chains (65C40)

Related Items (4)

Contaminant transport forecasting in the subsurface using a Bayesian framework ⋮ GPU-accelerated 3D reconstruction of porous media using multiple-point statistics ⋮ Multiscale sampling for the inverse modeling of partial differential equations ⋮ Multi-physics Markov chain Monte Carlo methods for subsurface flows

Uses Software

• SPRNG
• CUDA

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Application of the two-stage Markov chain Monte Carlo method for characterization of fractured reservoirs using a surrogate flow model
• A semi-discrete central scheme for the approximation of two-phase flows in three space dimensions
• General purpose molecular dynamics simulations fully implemented on graphics processing units
• On the numerical simulation of waterflooding of heterogeneous petroleum reservoirs
• Inference from iterative simulation using multiple sequences
• New high-resolution central schemes for nonlinear conservation laws and convection-diffusion equations
• Rapid quantification of uncertainty in permeability and porosity of oil reservoirs for enabling predictive simulation
• Efficient parallelisation of Metropolis-Hastings algorithms using a prefetching approach
• Uncertainty quantification for porous media flows
• Dynamic data driven simulations in stochastic environments
• Practical Markov Chain Monte Carlo
• TeraFLOP computing on a desktop PC with GPUs for 3D CFD
• Computational Methods for Multiphase Flows in Porous Media
• Preconditioning Markov Chain Monte Carlo Simulations Using Coarse-Scale Models
• A MULTI-STAGE BAYESIAN PREDICTION FRAMEWORK FOR SUBSURFACE FLOWS

This page was built for publication: A prefetching technique for prediction of porous media flows