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The AAPG/Datapages Combined Publications Database

AAPG Bulletin

Abstract

DOI:10.1306/01021312054

Improved geostatistical models of inclined heterolithic strata for McMurray Formation, Alberta, Canada

Mehran M. Hassanpour,1 Michael J. Pyrcz,2 Clayton V. Deutsch3

1Centre for Computational Geostatistics, 3-133 Natural Resources Engineering Facility Building, University of Alberta, Edmonton, Alberta, Canada; rahmanm@ualberta.ca
2Chevron Energy Technology Company, 1500 Louisiana Street, Houston, Texas; michael.pyrcz@chevron.com
3Centre for Computational Geostatistics, 3-133 Natural Resources Engineering Facility Building, University of Alberta, Edmonton, Alberta, Canada; cdeutsch@ualberta.ca

ABSTRACT

The McMurray Formation of northern Alberta in Canada contains multiscale complex geologic features that were partially formed in a fluvial-estuarine depositional environment. The inclined heterolithic strata deposited as part of fluvial point bars contain continuous centimeter-scale features that are important for flow characterization of steam-assisted gravity drainage processes. These channels are common, extensive, and imbricated over many square kilometers. Modeling the detailed facies in such depositional systems requires a methodology that reflects heterogeneity over many scales. This article presents an object-based facies modeling technique that (1) reproduces the geometry of multiscale geologic architectural elements seen in the McMurray Formation outcrops and (2) provides a grid-free framework that models these geologic objects without relating them to a grid system. The grid-free object-based modeling can be applied to any depositional environment and allows for the complete preservation of architectural information for consistent application to any gridding scheme, local grid refinements, downscaling, upscaling, drape surface, locally variable azimuths, property trend modeling, and flexible model interaction and manipulation. Features millimeters thick or kilometers in extent are represented very efficiently in the same model.

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