CCWSIM: an efficient and fast wavelet-based CCSIM for categorical characterization of large-scale geological domains.

Bavandsavadkoohi, Mojtaba; Gloaguen, Erwan; Tokhmechi, Behzad; Arab-Amiri, Alireza et Giroux, Bernard ORCID: https://orcid.org/0000-0002-2042-2759 (2025). CCWSIM: an efficient and fast wavelet-based CCSIM for categorical characterization of large-scale geological domains. Earth Science Informatics , vol. 18 , nº 2. p. 353. DOI: 10.1007/s12145-025-01858-1.

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Résumé

Recent advancements in Multiple-Point Statistics (MPS) simulations have focused on achieving realism by improving spatial continuity, conditioning data integration, stochasticity, and computational efficiency. However, simultaneously optimizing these factors remains a challenge. This work proposes a novel approach that integrates the strengths of Cross-Correlation Simulation (CCSIM) and the Discrete Wavelet Transform (DWT) to address these limitations. The method leverages the DWT's ability to capture essential spatial patterns in a compressed domain. It computes the DWT for both the training image (TI) and a region shared with previously simulated grids at a specific decomposition level. Similarity between these compressed representations is efficiently measured using a Cross-Correlation Function (CCF). By utilizing the compressed wavelet coefficients, the proposed method accelerates the search for the best-matching pattern while retaining the essential characteristics of the original data. Once identified, the original pattern is reconstructed by integrating the DWT detail coefficients through an Inverse-DWT transformation. Experiments conducted on diverse categorical training images demonstrate that the proposed approach achieves performance comparable to multi-scale CCSIM (MS-CCSIM) while exhibiting improvements in spatial continuity and computational efficiency. The open-source implementation of the method is available at https://github.com/MBS1984/CCWSIM for further development.

Type de document:	Article
Mots-clés libres:	geostatistical modeling; computational efficiency; wavelet decomposition; heterogeneity characterization; MPS simulation
Centre:	Centre Eau Terre Environnement
Date de dépôt:	10 juill. 2025 18:34
Dernière modification:	10 juill. 2025 18:34
URI:	https://espace.inrs.ca/id/eprint/16434

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