An Ensemble of Geostatistical Simulated Realizations Using a Clustering Algorithm to Reproduce Model-Based Statistics: Case Study of a Gravel Reserve at Kivalina,Alaska |
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| Authors: | Snehamoy Chatterjee |
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| Institution: | Department of Mining Engineering, National Institute of Technology , Rourkela , India |
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| Abstract: | This paper demonstrates the convergence of model-based statistics from multiple simulated realizations. Theoretically, the convergence of realization statistics is guaranteed over the number of realizations that are independent among themselves. The rate at which realization-based statistics converges with model-based statistics is important and must be assessed. However, due to poor selection of the random number generator, the generated realization might be far from mutual independence. We use the k-means clustering algorithm to select nearly independent realizations from a set of realization models. We apply the proposed algorithm to a coastal erosion problem in Alaska to estimate the amount of gravel. |
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| Keywords: | clustering algorithm geostatistics gravel reserve Kivalina Alaska |
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