Integration of Seismic Anisotropy and Reservoir-Performance Data for Characterization of Naturally Fractured Reservoirs Using Discrete-Feature-Network Models

Abstract

SummaryThis paper proposes a method for quantitative integration of seismic (elastic) anisotropy attributes with reservoir-performance data as an aid in characterizing systems of natural fractures in hydrocarbon reservoirs. This method is demonstrated through application to history matching of reservoir performance using synthetic test cases.Discrete-feature-network (DFN) modeling1 is a powerful tool for developing fieldwide stochastic realizations of fracture networks in petroleum reservoirs. Such models are typically well conditioned in the vicinity of the wellbore through incorporation of core data, borehole imagery, and pressure-transient data. Model uncertainty generally increases with distance from the borehole. Three-dimensional seismic data provide uncalibrated information throughout the interwell space. Some elementary seismic attributes such as horizon curvature and impedance anomalies have been used to guide estimates of fracture trend and intensity (fracture area per unit volume) in DFN modeling2 through geostatistical calibration with borehole and other data. However, these attributes often provide only weak statistical correlation with fracture-system characteristics.The presence of a system of natural fractures in a reservoir induces elastic anisotropy that can be observed in seismic data. Elastic attributes such as azimuthally dependent normal moveout velocity (ANMO), reflection amplitude vs. azimuth (AVAZ), and shear-wave birefringence can be inverted from 3D-seismic data. Anisotropic elastic theory provides physical relationships among these attributes and fracture-system properties such as trend and intensity. Effective-elastic-media models allow forward modeling of elastic properties for fractured media.A technique has been developed in which both reservoirperformance data and seismic anisotropic attributes are used in an objective function for gradient-based optimization of selected fracture-system parameters. The proposed integration method involves parallel workflows for effective elastic and effective permeability media modeling from an initial DFN estimate of the fracture system. The objective function is minimized through systematic updates of selected fracture-population parameters. Synthetic data cases show that 3D-seismic attributes contribute significantly to the reduction of ambiguity in estimates of fracture-system characteristics in the interwell rock mass. The method will benefit enhanced-oil-recovery (EOR) program planning and management, optimization of horizontal-well trajectory and completion design, and borehole-stability studies.