Abstract: In Shunan desert area of central Tarim Basin, large sand-dunes with large relief cause great attenuation and absorption of seismic signals. In addition, the deep Ordovician carbonates have strong heterogeneity. All these unfavorable conditions give rise to poor imaging of the fractured-vuggy reservoirs and small faults, bringing significant difficulties to reservoir prediction and trap identification. Therefore, in this paper, a comprehensive research of 3D seismic acquisition, target-oriented processing and interpretation is carried out to solve the above problems. First, a better acquisition scheme based on fractured-vuggy carbonate reservoir imaging is designed, in which the shooting and receiving parameters are optimized to improve seismic data quality. Then, a series of imaging techniques like pre-stack time migration and RTM migration imagining with suitable key parameters for the Ordovician carbonate reservoirs are established to improve imaging precision of the fractured-vuggy carbonate reservoirs and small faults while preserving true amplitude. In addition, accor-ding to the seismic reflection features and types of carbonate reservoirs in the Ordovician, a set of reservoir prediction and hydrocarbon detection techniques for fractured-vuggy reservoirs and fractured traps is developed including seismic pattern recognition of reservoir in different stratigraphic section and sensitive attributes analysis. Finally, special techniques of traps prediction and characterization are developed and they divide different zones by using faults and define borders of traps by using attributes. Techniques featuring in five factors including type, genesis, model and technique are developed for target optimization and evaluation. Several wells discovered natural gas in this area, providing a solid proof for the effectiveness and applicability of 3D seismic exploration technology of carbonate gas reservoir in Shunnan Desert Area.

Key words: carbonate rock, 3D seismic, reservoir prediction, gas reservoir, Tarim Basin