Conditioning Multiple?Point Statistics Simulation to Inequality Data
نویسندگان
چکیده
Stochastic modeling is often employed in environmental sciences for the analysis and understanding of complex systems. For example, random fields are key components uncertainty or Bayesian inverse modeling. Multiple-point statistics (MPS) provides efficient simulation tools simulating reproducing spatial depicted a training image (TI), while accounting local block conditioning data. Among MPS methods, direct sampling algorithm flexible pixel-based technique that consists first assigning data values (so-called hard data) grid, then populating rest domain order by successively pasting value from TI cell sharing similar pattern. In this study, an extension method proposed to account inequality data, is, constraints given cells consisting lower and/or upper bounds simulated values. Indeed, available practice. The new approach involves adaptation distance used compare evaluate match between two patterns such constraints. method, implemented DeeSse code, allows generating both reflecting honoring Finally examples topography simulations illustrate show capabilities method.
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ژورنال
عنوان ژورنال: Earth and Space Science
سال: 2021
ISSN: ['2333-5084']
DOI: https://doi.org/10.1029/2020ea001515