Fractured reservoir prediction is risky and challenging because of the variability in fracture characteristics and the lack of direct observational data in the subsurface. To reduce the risk and challenge, we have developed an integrated workflow to predict fractured reservoirs based on 3D seismic data. The workflow begins with reservoir structure analysis from seismic reflection geometry, which is referred to as seismic structure analysis, to define fracture intensity and fracture orientation using maximum curvature and maximum flexure algorithms. Next, the workflow proceeds with reservoir texture analysis from seismic amplitude signal, which is referred to as seismic texture analysis, to evaluate fracture scale and reservoir facies using waveform regression and calibration algorithms. The results from seismic structure and texture analyses are then used for modeling reservoir properties and fracture networks. Each algorithmic method in the workflow is tested in a siliciclastic tight-sand reservoir in the Teapot Dome oil field (Powder River Basin) and in a carbonate reservoir in the South Pars gas field (Persian Gulf Basin). The test results reveal the previously unknown reservoir heterogeneity and anisotropy that are interpreted to be attributable to the variability in fracture characteristics. It is concluded that the integrated workflow based on seismic structure and texture analyses could potentially contribute to reducing the risk and challenge in characterizing fractured reservoirs in the subsurface.