Indicator-based data assimilation with multiple-point statistics for updating an ensemble of models with non-Gaussian parameter distributions

Keyphrases

• Data Assimilation 100%
• Indicator-based 100%
• Ensemble Model 100%
• Parameter Distribution 100%
• Non-Gaussian Statistics 100%
• Multiple-point Statistics 100%
• Flow Response 80%
• Subsurface Heterogeneity 60%
• Ensemble Kalman Filter (EnKF) 40%
• Non-Gaussian 40%
• Spatial Characteristics 40%
• Groundwater Flow 40%
• Data Assimilation Method 40%
• Geologic Model 40%
• Groundwater System 40%
• Parameter Update 40%
• Solute 20%
• Contaminant Transport 20%
• Spatial Distribution 20%
• Bivariate 20%
• Sand 20%
• Clay 20%
• Concentration Profile 20%
• Covariance 20%
• Dynamic Data 20%
• Subsurface System 20%
• Multiple-point Simulation 20%
• Transport Response 20%
• Well Location 20%
• Filter Method 20%
• Ensemble-based 20%
• Reference Flow 20%
• Multi-Gaussian 20%
• Geologic Structure 20%
• Strongly Nonlinear 20%
• Response Data 20%
• Ensemble-based Data Assimilation 20%
• Covariance-based 20%
• Geological Heterogeneity 20%
• Simulation Algorithm 20%
• Complex Channel 20%
• Linear Assumption 20%
• Model Update 20%
• Spatial Continuity 20%
• Nonlinear Transformation 20%
• Channel Features 20%

Earth and Planetary Sciences

• Data Assimilation 100%
• Covariance 33%
• Groundwater Flow 33%
• Kalman Filter 33%
• Spatial Distribution 16%