Bayesian inverse problem and optimization with iterative spatial resampling

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The Direct Sampling method to perform multiple‐point geostatistical simulations (2010, methodology): “It has also been applied with inversemodeling techniques [Alcolea and Renard, 2010; Caers and Hoffman, 2006; Ronayne et al., 2008;Mariethoz et al., 2010].”
Inverse methods in hydrogeology: Evolution and recent trends (2014, methodology): “Examples of this method include traditional reject sampling (Von Neumann,764 1951), iterative spatial resampling (Mariethoz et al., 2010) and McMC-based methods (Oliver et al., 1997;765 Fu and Gómez-Hernández, 2009b; Alcolea and Renard, 2010).”
Efficient posterior exploration of a high‐dimensional groundwater model from two‐stage Markov chain Monte Carlo simulation and polynomial chaos expansion (2013, background): “[4] In recent years, Bayesian approaches are becoming increasingly popular for aquifer and reservoir characterization, and parameter and model predictive uncertainty analysis [e.g., Oliver et al., 1997; Efendiev et al., 2005; Fu and Gomez-Hernandez, 2009; Mariethoz et al., 2010; Mondal et al., 2010;”
Geological realism in hydrogeological and geophysical inverse modeling: A review (2015, methodology): “In contrast to the blocking window method, the Iterative Spatial Resampling (ISR) method [117] consists of re-simulating grid cells”