A distance-based prior model parameterization for constraining solutions of spatial inverse problems

DOI10.1007/s11004-008-9154-8zbMath1142.86304OpenAlexW1979406450MaRDI QIDQ934752

Satomi Suzuki, Jef Caers

Publication date: 30 July 2008

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

Full work available at URL: https://doi.org/10.1007/s11004-008-9154-8

zbMATH Keywords

Inverse problemsDistance functionGeostatisticsStochastic search

Mathematics Subject Classification ID

Inverse problems in geophysics (86A22) Geostatistics (86A32)

Related Items (14)

Reduced Space Dynamics-Based Geo-Statistical Prior Sampling for Uncertainty Quantification of End Goal Decisions ⋮ Flow-based dissimilarity measures for reservoir models: a spatial-temporal tensor approach ⋮ A frequency matching method: solving inverse problems by use of geologically realistic prior information ⋮ Stochastic inversion of gravity data accounting for structural uncertainty ⋮ Constructing branching trees of geostatistical simulations ⋮ Reducing uncertainty in conceptual prior models of complex geologic systems via integration of flow response data ⋮ Image transforms for determining fit-for-purpose complexity of geostatistical models in flow modeling ⋮ Kernel principal component analysis for stochastic input model generation ⋮ Uncertainty quantification in reservoir prediction. II: Handling uncertainty in the geological scenario ⋮ A multi-resolution workflow to generate high-resolution models constrained to dynamic data ⋮ Stochastic simulation of patterns using distance-based pattern modeling ⋮ Towards stochastic time-varying geological modeling ⋮ Comparing training-image based algorithms using an analysis of distance ⋮ Representing spatial uncertainty using distances and kernels

Uses Software

• Jakarta

Cites Work

• The probability perturbation method: a new look at Bayesian inverse modeling
• Estimation of two-phase petroleum reservoir properties by regularization
• Gradual deformation and iterative calibration of sequential stochastic simulations
• Conditional simulation of complex geological structures using multiple-point statistics
• Uncertainty quantification for porous media flows
• Markov Random Fields with Higher-order Interactions
• Unnamed Item

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