{'fraction_non_alphanumeric': 0.016442451420029897, 'fraction_numerical': 0.0, 'mean_word_length': 5.979166666666667, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
PluriGaussian Simulations with the Stochastic Partial Differential Equation (SPDE) Approach

Summary In this work, the Stochastic Partial Differential Equation approach is used to model the underlying Gaussian random fields in the PluriGaussian models. This approach allows to perform conditional simulations with computational complexity nearly independent of the size of the data sets. Furthermore, by using non-homogeneous operators, this framework allows to handle varying anisotropies and model complex geological structures. The model is presented and the proposed simulation algorithm is described. The methodology is illustrated through two synthetic data sets.