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Vertical Stacking Statistics of Multi-facies Object-Based Models

Equations describing facies proportions and amalgamation ratios are derived for randomly placed objects belonging to two or three foreground facies embedded in a background facies, as a function of the volume fractions and object thicknesses of independent facies models combined in a stratigraphical...

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Detalles Bibliográficos
Autores principales: Manzocchi, Tom, Walsh, Deirdre A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10119076/
https://www.ncbi.nlm.nih.gov/pubmed/37096029
http://dx.doi.org/10.1007/s11004-023-10046-0
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author Manzocchi, Tom
Walsh, Deirdre A.
author_facet Manzocchi, Tom
Walsh, Deirdre A.
author_sort Manzocchi, Tom
collection PubMed
description Equations describing facies proportions and amalgamation ratios are derived for randomly placed objects belonging to two or three foreground facies embedded in a background facies, as a function of the volume fractions and object thicknesses of independent facies models combined in a stratigraphically meaningful order. The equations are validated using one-dimensional continuum models. Evaluation of the equations reveals a simple relationship between an effective facies proportion and an effective amalgamation ratio, both measured as a function only of the facies in question and the background facies. This relationship provides a firm analytical basis for applying the compression algorithm to multi-facies object-based models. A set of two-dimensional cross-sectional models illustrates the approach, which allows models to be generated with realistic object stacking characteristics defined independently for each facies in a multi-facies object-based model.
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spelling pubmed-101190762023-04-22 Vertical Stacking Statistics of Multi-facies Object-Based Models Manzocchi, Tom Walsh, Deirdre A. Math Geosci Article Equations describing facies proportions and amalgamation ratios are derived for randomly placed objects belonging to two or three foreground facies embedded in a background facies, as a function of the volume fractions and object thicknesses of independent facies models combined in a stratigraphically meaningful order. The equations are validated using one-dimensional continuum models. Evaluation of the equations reveals a simple relationship between an effective facies proportion and an effective amalgamation ratio, both measured as a function only of the facies in question and the background facies. This relationship provides a firm analytical basis for applying the compression algorithm to multi-facies object-based models. A set of two-dimensional cross-sectional models illustrates the approach, which allows models to be generated with realistic object stacking characteristics defined independently for each facies in a multi-facies object-based model. Springer Berlin Heidelberg 2023-02-14 2023 /pmc/articles/PMC10119076/ /pubmed/37096029 http://dx.doi.org/10.1007/s11004-023-10046-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Manzocchi, Tom
Walsh, Deirdre A.
Vertical Stacking Statistics of Multi-facies Object-Based Models
title Vertical Stacking Statistics of Multi-facies Object-Based Models
title_full Vertical Stacking Statistics of Multi-facies Object-Based Models
title_fullStr Vertical Stacking Statistics of Multi-facies Object-Based Models
title_full_unstemmed Vertical Stacking Statistics of Multi-facies Object-Based Models
title_short Vertical Stacking Statistics of Multi-facies Object-Based Models
title_sort vertical stacking statistics of multi-facies object-based models
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10119076/
https://www.ncbi.nlm.nih.gov/pubmed/37096029
http://dx.doi.org/10.1007/s11004-023-10046-0
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