Contaminant spill in a sandbox with non-Gaussian conductivities: simultaneous identification by the restart normal-score ensemble Kalman filter

DOI10.1007/s11004-021-09928-yzbMath1477.86025OpenAlexW3136274637MaRDI QIDQ2066823

Teng Xu, Zi Chen, Andrea Zanini, J. Jaime Gómez-Hernández

Publication date: 14 January 2022

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

Full work available at URL: https://doi.org/10.1007/s11004-021-09928-y

zbMATH Keywords

sandboxdata assimilationinverse modelingforensic hydrogeology

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Geostatistics (86A32)

Uses Software

• MT3DMS

Cites Work

• Unnamed Item
• A probability conditioning method (PCM) for nonlinear flow data integration into multipoint statistical facies simulation
• Stochastic conditional inverse modeling of subsurface mass transport: A brief review and the self-calibrating method
• Ensemble-based assimilation of nonlinearly related dynamic data in reservoir models exhibiting non-Gaussian characteristics
• 3D inverse modelling of groundwater flow at a fractured site using a stochastic continuum model with multiple statistical populations
• History matching of facies distribution with the EnKF and level set parameterization

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