Assimilating spatially dense data for subsurface applications -- balancing information and degrees of freedom
type: Item
instance of: scholarly article
title: Assimilating spatially dense data for subsurface applications -- balancing information and degrees of freedom
zbMATH Open document ID: 1406.86016
author: Trond Mannseth
author: Kristian Fossum
published in: Computational Geosciences
publication date: 2019-02-04T00:00:00Z
Mathematics Subject Classification ID: 86A15
Mathematics Subject Classification ID: 86A22
Mathematics Subject Classification ID: 86A32
zbMATH DE Number: 7011378
zbMATH Keywords: ensemble-based history matching
zbMATH Keywords: inverted seismic data
zbMATH Keywords: reduced data space
zbMATH Keywords: coarse-scale simulation
describes a project that uses: EnKF
MaRDI profile type: Publication
full work available at URL: s10596-018-9755-3
OpenAlex ID: W2887676175
cites work: Iterative Solution Methods
cites work: Levenberg-Marquardt forms of the iterative ensemble smoother for efficient history matching and uncertainty quantification
cites work: The ensemble Kalman filter for combined state and parameter estimation
cites work: Upscaling: a review
cites work: Coarse-scale data assimilation as a generic alternative to localization
cites work: Ensemble-based conditioning of reservoir models to seismic data
Wikidata QID: Q129450076
DOI: 10.1007/S10596-018-9755-3
description: scientific article; zbMATH DE number 7011378