Pages that link to "Item:Q601225"
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The following pages link to Cross-covariances and localization for EnKF in multiphase flow data assimilation (Q601225):
Displaying 34 items.
- Fast linearized forecasts for subsurface flow data assimilation with ensemble Kalman filter (Q341509) (← links)
- Characterizing curvilinear features using the localized normal-score ensemble Kalman filter (Q448823) (← links)
- Relation between two common localisation methods for the EnKF (Q536577) (← links)
- Balance-aware covariance localisation for atmospheric and oceanic ensemble Kalman filters (Q536579) (← links)
- Ensemble-based conditioning of reservoir models to seismic data (Q536595) (← links)
- Distributed parameter and state estimation in petroleum reservoirs (Q536663) (← links)
- Evaluation and error analysis: Kalman gain regularization versus covariance regularization (Q695707) (← links)
- Facies estimation through data assimilation and structure parameterization (Q723195) (← links)
- Characterization of non-Gaussian geologic facies distribution using ensemble Kalman filter with probability weighted re-sampling (Q887631) (← links)
- Iterative regularization for ensemble data assimilation in reservoir models (Q894224) (← links)
- Application of the EnKF and localization to automatic history matching of facies distribution and production data (Q934754) (← links)
- Improving the ensemble estimate of the Kalman gain by bootstrap sampling (Q964859) (← links)
- Parameterised non-intrusive reduced order methods for ensemble Kalman filter data assimilation (Q1626167) (← links)
- Data assimilation in truncated plurigaussian models: impact of the truncation map (Q1629751) (← links)
- Ensemble-based multi-scale history-matching using second-generation wavelet transform (Q1640360) (← links)
- Evaluation of Gaussian approximations for data assimilation in reservoir models (Q1663455) (← links)
- A simulation-based geostatistical approach to real-time reconciliation of the grade control model (Q1698331) (← links)
- Localization and regularization for iterative ensemble smoothers (Q1702330) (← links)
- Coarse-scale data assimilation as a generic alternative to localization (Q1702341) (← links)
- Identifying influence areas with connectivity analysis -- application to the local perturbation of heterogeneity distribution for history matching (Q1710278) (← links)
- Using a machine learning proxy for localization in ensemble data assimilation (Q2027164) (← links)
- A graph clustering approach to localization for adaptive covariance tuning in data assimilation based on state-observation mapping (Q2066842) (← links)
- Iterative multilevel assimilation of inverted seismic data (Q2130959) (← links)
- Data assimilation with soft constraints (DASC) through a generalized iterative ensemble smoother (Q2147569) (← links)
- Data-space inversion with ensemble smoother (Q2192795) (← links)
- Ensemble filter methods with perturbed observations applied to nonlinear problems (Q2269055) (← links)
- Exploring the need for localization in ensemble data assimilation using a hierarchical ensemble filter (Q2371201) (← links)
- Recent progress on reservoir history matching: a review (Q2430878) (← links)
- Uncertainty quantification in the ensemble Kalman filter (Q2868872) (← links)
- Theoretical and efficient practical procedures for the generation of inflation factors for ES-MDA (Q4597561) (← links)
- A Localization Strategy for Data Assimilation; Application to State Estimation and Parameter Estimation (Q4637672) (← links)
- Localized ensemble Kalman inversion (Q6042934) (← links)
- Sequential multilevel assimilation of inverted seismic data (Q6106109) (← links)
- An adjoint-free four-dimensional variational data assimilation method via a modified Cholesky decomposition and an iterative Woodbury matrix formula (Q6166395) (← links)
