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Streamlines Based Multivariate Regression Models to Quantify the Impact of Reservoir Heterogeneity on Ultimate Recovery

A. AlNajem1, M. Soliman1, S. Siddiqui1, and B. Chidmi1

1Texas Tech University


Reservoir heterogeneity plays an important role in reservoir performance, especially under secondary and tertiary displacements. Many different estimators have been proposed to characterize reservoir heterogeneity. The heterogeneity classifiers typically fall into two groups - static and dynamic. The two static parameters most often used to quantify reservoir heterogeneity are the Dykstra-Parsons coefficient (VDP) and the Lorenz coefficient (LC).

The static heterogeneity classifiers however, are inadequate to account for the complex and nonlinear interrelationships among permeability, pressure and changing fluid saturation within porous media. Hence, a number of dynamic heterogeneity classifiers that implicitly include fluid distribution in flow path and its connected structures have been proposed. These classifiers include fast simulation, permeability-connectivity estimates, and streamline simulation. Among these, streamline simulation has gained wide attention during the last two decades. Computation of streamlines is fast and effective and yields direct relationships between time of flight (TOF) and dynamic data such as production and tracer breakthrough curves.


AAPG Search and Discovery Article #90188 ©GEO-2014, 11th Middle East Geosciences Conference and Exhibition, 10-12 March 2014, Manama, Bahrain