Abstract:

A seismic attributes includes physical attribute and geometry attribute, which quantifies specifically the characters of geometry, kinematics, dynamics or statistics in seismic data. Although geometry attributes can be easily accepted and straightly identified by the sense organ of men,the physical attributes derived from abstract process and mathematics are better than geometry attribute in seismic reservoir prediction.Therefore,seismic attribute is mainly referred to physical attribute calculated by mathematical algorithm. Reservoir prediction by seismic attributes is widely used in geophysics. Since 1980s,pattern recognition technique is paid great attention to,and the reservoir prediction techniques,such as a fuzzy pattern recognition, statistic pattern recognition, neural network pattern recognition and function approach,have been successively developed.The predicted objects include hydrocarbon, reservoir thickness, lithology and reservoir porosity.In resevoir prediction,the selection of seismic attribute is accomplished by experiences of interpreters,whose effect is subject to better geological conditions, simple predicted objects,and higher S/N in original seismic data. However, under the other conditions, the effect of prediction is worse. In fact,there exist complex relations between predicted objects and their seismic attributes. The seismic attributes sensitive to predicted objects are not totally the same in different areas and reservoirs. They are also somewhat different even for same reservoir and same area. The optimization technique of seismic attributes is an effective means for solving the above questions. The optimum methods of seismic attributes mainly include the dimension-reduced projected profile and cluster analysis etc. Its purpose is to optimize the minimum seismic attributes or seismic attributes group, which are the most sensitive (or most effective, most representative) to studied problem,in order to increase reservoirs prediction precision and to improve the effect of processing and interpretation related to seismic attributes. The obvious effect of reservoir prediction in CB31 area has been achieved by using the optimum method of seismic attributes. This area is located at the graben belt that is between the drape structures of CB30 buried hill and the drap structures of Changdi buried hill. Its main reservoirs are the sand bars,formed by meander river sediment,in Neogene Guantao Fm,with poor continuity and small distribution. Because the distribution of depositional sand bodies are unstable in lateral and vertical direction and because the drilled thickness of sand bodies is usually less than 10m,the sand bodies have no corresponding reflection on seismic sections, resulting in the bigger difficulty in reservoir prediction and description.Therefore, the recognition of its pool-forming factors and hydrocarbon accumulation rules has been disputed for many years. With the help of the theory and methods of seismic attribute optimization, the seismic attributes of predicted reservoir are optimized. Meanwhile, one of the optimized seismic attributes, the wave peak number, is verified with seismic forward modeling, and demonstrating the reliability of the method. Based on the above works, the stratigraphy, reflected wave velocity, structure and electric property have been studied;the pool-forming factors and hydrocarbon accumulation have been analyzed;the areal distribution of sand bodies have been basically identified;more than 30 sand bodies have been described.As a result,the oil in place reserve in the CB31 wellblock is estimated to be 40 million tons.

Key words: reservoir prediction, seismic attribute, attribute optimization, forward modeling