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Principles of Carbonate Matrix Petrophysical Data Analysis and Reservoir Flow Model Construction

James W. Jennings, Jr.
Bureau of Economic Geology, John A. and Katherine G. Jackson School of Geosciences
The University of Texas at Austin, Austin, Texas

 

Matrix petrophysical properties in most carbonate reservoirs exhibit a high degree of spatial variability over a wide range of scales. This variability creates a unique set of challenges for geoscientists and reservoir engineers attempting to construct 3D geocellular models of fluid-flow properties for meaningful reservoir performance predictions. The special challenges presented by carbonates occur in nearly all stages of reservoir characterization and model construction, from flow-unit identification, to statistical analysis and reconciliation of data at different scales, interwell modeling of petrophysical properties, and flow-model scaleup.

Although no two carbonate reservoirs are exactly alike, we can make some useful generalizations about their spatial variability, the resulting effects on fluid flow, and the implications for data analysis and model construction. This insight will probably not produce a single simplified “recipe” for carbonate reservoir modeling that will be adequate for the wide range of cases we encounter. However, the insight does lead to some fundamental principles that can be very helpful in anticipating problems, avoiding pitfalls, and Previous HitselectingTop appropriate data analysis and modeling methods for each individual carbonate reservoir.

In this presentation I will summarize some of the most useful generalizations concerning carbonate matrix petrophysical variability and fluid flow obtained from research at the University of Texas Bureau of Economic Geology. Then, I will outline some data analysis and modeling principles that follow from this insight. These generalizations and principles are primarily derived from outcrop and subsurface studies of shallow-water platform carbonates in West Texas (Permian) and the Middle East (Cretaceous), but many of the ideas apply to other settings as well.