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

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.

[1]  S. Pemberton,et al.  Trace Fossils from the Athabasca Oil Sands, Alberta, Canada , 1982, Science.

[2]  Grant D. Mossop,et al.  Deep channel sedimentation in the Lower Cretaceous McMurray Formation, Athabasca Oil Sands, Alberta , 1983 .

[3]  James M. Wood,et al.  Inclined heterolithic stratification—Terminology, description, interpretation and significance , 1987 .

[4]  Dominique Guerillot,et al.  Conditional Simulation of the Geometry of Fluvio-Deltaic Reservoirs , 1987 .

[5]  F. Alabert,et al.  Non-Gaussian data expansion in the Earth Sciences , 1989 .

[6]  Andre G. Journel,et al.  Stochastic imaging of the Wilmington clastic sequence , 1990 .

[7]  Clayton V. Deutsch,et al.  ANNEALING TECHNIQUES APPLIED TO RESERVOIR MODELING AND THE INTEGRATION OF GEOLOGICAL AND ENGINEERING (WELL TEST) DATA , 1992 .

[8]  J. Bridge Description and interpretation of fluvial deposits: a critical perspective , 1993 .

[9]  T. Jøssang,et al.  A Simulation Model for Meandering Rivers , 1996 .

[10]  Clayton V. Deutsch,et al.  Hierarchical object-based stochastic modeling of fluvial reservoirs , 1996 .

[11]  YuLong Xie,et al.  Surface-Geometry and Trend Modeling for Integration of Stratigraphic Data in Reservoir Models , 2001 .

[12]  Clayton V. Deutsch,et al.  FLUVSIM: a program for object-based stochastic modeling of fluvial depositional systems , 2002 .

[13]  Clayton V. Deutsch,et al.  Geostatistical Reservoir Modeling , 2002 .

[14]  Clayton V. Deutsch,et al.  Stochastic surface modeling of deepwater depositional systems for improved reservoir models , 2009 .

[15]  Brian J. Willis,et al.  Three-Dimensional Connectivity of Point-Bar Deposits , 2010 .

[16]  David J. Patruyo A Computer Model of a 3-Dimensional Point Bar System , 2010 .

[17]  M. Fustic,et al.  Seismic geomorphology and sedimentology of a tidally influenced river deposit, Lower Cretaceous Athabasca oil sands, Alberta, Canada , 2011 .

[18]  Stephen M. Hubbard,et al.  Recognition of down-valley translation in tidally influenced meandering fluvial deposits, Athabasca Oil Sands (Cretaceous), Alberta, Canada , 2012 .