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Fractured Volcanic Reservoir Characterization: A Case Study in the Deep Songliao Basin

Abstract

The study area is located in the XJ fault depression, within the deep Songliao basin of north-eastern China. The area is characterized by a monoclinal structure that includes a few fractured volcanic reservoir traps in Cretaceous formations. The P&D of gas reservoirs faced many difficulties, including imaging of the volcano, identification of heterogeneous volcanic rock facies, and fracture detection, which was the most important. Based on the integrated acquisition and processing of 3D-VSP and full-azimuth surface seismic data, this paper focuses on the interpretation of volcanic reservoirs to characterize the fractured volcanic reservoir geometry, distribution, properties and highly productive gas regions. Use of seismic attributes for fractured volcanic reservoirs' detection below the resolution of conventional seismic data is a major goal in this project. A new method is developed to improve imaging of volcanoes, and minor faults and fractures using “discrete frequency curvature (DFC)”. The DFC data are computed using discrete frequency seismic data obtained from spectral decomposition. The DFC attribute allows us to recognize different geologic information about fractured volcanic reservoirs in different frequency bands of seismic data. 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. Moreover, the multi-geophysical methods, such as strata slice, HTI fracture detection and pre-stack inversion etc. also have been applied to characterize the volcanic reservoir. Strata time slices of coherence data are used to describe the volcanic evolution. Structure modelling can provide an efficient tool to delineate geometry and distribution of volcanic bodies. The fracture inversion and HTI fracture detection method can be used to detect the orientation and density of fractured reservoir, while AVO and pre-stack inversion is applied to detect gas-bearing volcanic reservoirs. After integrated study of the seismic attributes, well logs, and production data, we predicted the favourable production zones within the volcanic reservoir. The main factors controlling the volcanic reservoir are the distribution of volcanic facies, small faults, and fractures. The hydrocarbon reservoirs are located at a high position within the volcanoes, and the hydrocarbon is also clustered around the small faults and fractures within the system.