A Reduced-order Variational Bayesian Approach for Efficient Subsurface Imaging

Engineering

• Subsurface 100%
• Bayesian Approach 100%
• Numerical Experiment 33%
• Efficient Implementation 33%
• Model Parameter 33%
• Forward Model 33%
• Posterior Probability 33%
• Point Estimate 33%
• Joints (Structural Components) 33%
• Truncation 33%
• Square Solution 33%
• Closed Form 33%
• Computational Complexity 33%
• Cost Reduction 33%
• Posterior Distribution 33%
• Least Square 33%

Mathematics

• Discrete Cosine Transform 100%
• Subsurface 100%
• Bayesian Approach 100%
• Bayesian 80%
• Nonlinear 20%
• Closed Form 20%
• Probability Distribution 20%
• Bayesian Inference 20%
• Joint Posterior Distribution 20%
• Variance 20%
• Weighted Least Squares 20%
• Numerical Experiment 20%
• Truncation 20%
• Square Solution 20%
• Point Estimate 20%
• Transform Space 20%

Keyphrases

• Discrete Cosine Transform Coefficient 66%
• Inverse Reconstruction 33%
• Transform Order 33%