Importance of Facies-Based Earth Models for Understanding Flow Behavior in Carbonate Reservoirs*
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).
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.