2020
DOI: 10.1144/petgeo2018-078
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Hierarchical parameterization and compression-based object modelling of high net:gross but poorly amalgamated deep-water lobe deposits

Abstract: Deep-water lobe deposits are arranged hierarchically and can be characterized by high net:gross ratios but poor sand connectivity due to thin, but laterally extensive, shale layers. This heterogeneity makes them difficult to represent in standard full-field object-based models, since the sands in an object-based model are not stacked compensationally and become connected at a low net:gross ratio. The compression algorithm allows the generation of low-connectivity object-based models at high net:gross ratios, b… Show more

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Cited by 7 publications
(4 citation statements)
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“…This is an inevitable consequence of applying different compression factors across lateral facies transitions, and has been discussed by Manzocchi et al. ( 2020 ) and Walsh and Manzocchi ( 2021a ).…”
Section: The Compression Algorithm For Hierarchical Object-based Modelsmentioning
confidence: 96%
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“…This is an inevitable consequence of applying different compression factors across lateral facies transitions, and has been discussed by Manzocchi et al. ( 2020 ) and Walsh and Manzocchi ( 2021a ).…”
Section: The Compression Algorithm For Hierarchical Object-based Modelsmentioning
confidence: 96%
“…That work focuses on the Amalgamation Ratio as the fundamental measure of connectivity, and hence the method is better developed for hierarchical object-based rather than pixel-based models (Manzocchi et al. 2020 ; Soni et al. 2020 ).…”
Section: Practical Implementation Of Compression-based Modellingmentioning
confidence: 99%
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“…The objectives of this contribution are to demonstrate an important limitation in object-and pixel-based facies modelling with respect to facies connectivity, and to highlight the main features of the compression-based modelling method developed to overcome this limitation. Further details of the method can be found elsewhere [1][2][3].…”
Section: Introductionmentioning
confidence: 99%