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Hierarchical parameterization and compression-based object modelling of high net; gross but poorly amalgamated deep-water lobe deposits

Tom Manzocchi, L. Zhang, Peter D. W. Haughton and A. Ponten
Hierarchical parameterization and compression-based object modelling of high net; gross but poorly amalgamated deep-water lobe deposits
Petroleum Geoscience (December 2019) 26 (4): 545-567

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.


ISSN: 1354-0793
Serial Title: Petroleum Geoscience
Serial Volume: 26
Serial Issue: 4
Title: Hierarchical parameterization and compression-based object modelling of high net; gross but poorly amalgamated deep-water lobe deposits
Affiliation: University College Dublin, School of Earth Sciences, Fault Analysis Group, Dublin, Ireland
Pages: 545-567
Published: 20191205
Text Language: English
Publisher: Geological Society Publishing House for EAGE (European Association of Geoscientists & Engineers), London, United Kingdom
References: 80
Accession Number: 2020-003939
Categories: Sedimentary petrology
Document Type: Serial
Bibliographic Level: Analytic
Illustration Description: illus. incl. 1 table
N51°30'00" - N55°19'60", W10°30'00" - W06°30'00"
Secondary Affiliation: Equinor ASA, NOR, Norway
Country of Publication: United Kingdom
Secondary Affiliation: GeoRef, Copyright 2022, American Geosciences Institute. Reference includes data from GeoScienceWorld, Alexandria, VA, United States. Reference includes data from The Geological Society, London, London, United Kingdom
Update Code: 202004
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