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Hierarchical parameterization and compression-based object modelling of high net: gross but poorly amalgamated deep-water lobe deposits
Date Issued
2020-01-27
Date Available
2020-09-10T08:58:05Z
Embargo end date
2021-01-27
Abstract
Deepwater 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 generation of low connectivity object-based models at high net:gross ratios, by including the net: gross and amalgamation ratios as independent input parameters. Object-based modelling constrained by the compression algorithm has been included in a recursive workflow, permitting generation of realistic models of hierarchical lobe deposits. Representative dimensional and stacking parameters collected at four different hierarchical levels have been used to constrain a 250 m thick, 14 km2 model that includes hierarchical elements ranging from 20 cm thick sand beds to 30+ m thick lobe complexes. Sand beds and the fine-grained units are represented explicitly in the model, and the characteristic facies associations often used to parameterize lobe deposits are emergent from the modelling process. The model is subsequently resampled without loss of accuracy for flow simulation, and results show clearly the influence of the hierarchical heterogeneity on drainage and sweep efficiency during a water-flood simulation.
Sponsorship
University College Dublin
Other Sponsorship
PIPCO RSG Ltd.
FIFT II joint industry project
China Scholarship Council
Type of Material
Journal Article
Publisher
Geological Society of London
Journal
Petroleum Geoscience
Volume
26
Issue
4
Copyright (Published Version)
2020 the Authors
Language
English
Status of Item
Peer reviewed
ISSN
1354-0793
This item is made available under a Creative Commons License
File(s)
No Thumbnail Available
Name
FinalAcceptedVersion.pdf
Size
4.68 MB
Format
Adobe PDF
Checksum (MD5)
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Owning collection
Mapped collections