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.