Application of Spectral Decomposition and Curvature to Fractured Volcanic Reservoirs

This paper uses the integrated application of curvature and spectral decomposition to detect fractured volcanic reservoirs based on 3-D seismic data. A new method is developed to improve imaging of volcanoes, and minor faults and fractures using “discrete frequency curvature”. Discrete frequency curvature data are computed using discrete frequency seismic data obtained from spectral decomposition. The discrete frequency curvature attribute allows us to recognize different geologic information about fractured volcanic reservoirs in different frequency bands of seismic data. The different discrete frequency curvature attribute maps show that the low-frequency curvature data can be used to recognize the distribution of volcanoes, whereas high-frequency curvature data is more effective at detecting minor faults and fractures. When compared with the full spectrum data, the reconstructed curvature data offers a greater level of detail for the fractured volcanic reservoir. The results of our case study show that this method has the potential to be a valuable and highly effective seismic method.