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Importance of
Facies
-Based Earth Models for Understanding Flow Behavior in
Carbonate
Reservoirs*
By
Marjorie Levy1, William Milliken1, Paul (Mitch) Harris1, Sebastien Strebelle1, and Eugene C. Rankey2
Search and Discovery Article #40306 (2008)
Posted September 5, 2008
*Adapted from for oral presentation at AAPG Annual Convention, Long Beach, CA, April 1-4, 2007. See companion article,
”Understanding Flow Behavior in
Carbonate
Reservoirs from
Facies
-Based Earth Models,”
Search and Discovery Article #40288 (2008).
1 Chevron Energy Technology Company, San Ramon, CA ([email protected]; [email protected]; [email protected])
2 University of Miami CSL, Miami, FL ([email protected])
Reservoir models attempt to mimic the distribution of reservoir properties in subsurface systems, and in
carbonate
reservoirs should capture geologically meaningful and realistic heterogeneity. Comparing SGS-generated models with
facies
-based Multiple-Point Statistics (MPS)/
Facies
Distribution Models (FDM) highlights the importance of incorporating
facies
into models. These
facies
-based models provide a template to test which
carbonate
characteristics have the greatest impact on subsurface flow.
To explore different types of
carbonate
platforms, reef- and grainstone-dominated systems were simulated using training images, FDM cubes, and MPS simulations. On the basis of modern analogs from the Bahamas, grainstone shoals are modeled as linear, sinuous, or crescent-shaped, and include bar crest, bar flank, and island
facies
. Modeled reef-dominated platforms utilize analogs from Belize, and include barrier reef, discontinuous reef, and apron
facies
. All simulations use quantitative data and a conceptual model from a modern system as input.
Two types of flow experiments are run:
(1) the impact of depositional
facies
is tested keeping all other parameters the same; and
(2) an experimental design guided set of experiments varying:
a) proportions of reservoir
facies
vs non-reservoir
facies
,
b) proportions of bar flank/bar crest reservoir
facies
,
c) dimensions of
facies
,
d) diagenetic zones,
e) stratigraphic cyclicity,
f) spatial distribution of reservoir
facies
(distributed across platform vs. localized),
g) shape of reservoir
facies
(bars vs. crescents),
h) porosity histogram, and
h) permeability transform.
Each model was tested using reservoir simulation and considered different development scenarios and recovery processes. Models were compared on the basis of static measures of OOIP, reservoir connectivity and permeability heterogeneity; and on the basis of dynamic measures of recovery factor vs. time, recovery factor vs. pore volumes injected, net present oil, cumulative oil produced, and water breakthrough time.