The Study Of Seismic Pre-stack Attributes And Fluid Identification Factors

Litho-logic hydrocarbon reservoir exploration is one of the main fields of hydrocarbon exploration on the current and in the future. It fully utilizes pre-stack seismic attributes to improve the accuracy and precision of reservoir prediction, especially the reliable forecasts in the physical properties of the reservoir and the direct prediction of fluid. In recent years, litho-logic hydrocarbon reservoir exploration gradually absorbs great attention and become a hot spot of application and research. It is also one of the new technologies of hydrocarbon exploration.Accurate identification of the fluid in reservoir is the foundation of improving the effectiveness of hydrocarbon exploration and development. However, in the various reservoirs, the distribution of gas (oil) and water is very complex, with the influence of the degree of fissure development, lithology and diagenetic epigenetic changes, using only a little or a single information is difficult to achieve the purpose of physical property and fluid identifiying in reservoir. It needs to extract a variety of information which can reflect reservoir fluid from actual seismic data, and build various kinds of fluid identifying factors to identify fluid comprehensively and effectively.In comparison of post-stack attributes, pre-stack attribute contains more information, because it is not treated by superposition of stack. Utilizing the pre-stack attribute can make better use of the original information gained by multiple folds to predict the reservoir. This can be more reliable than utilizing the post-stack attributes. We can get many kinds of pre-stack attributes via pre-stack processing, including some AVO attributes and data volume of angle stack. On this basis, we can make a variety of pre-stack inversion and then get many kinds of elastic properties data volume, all of these can help us to analyze lithology and identify fluid.On the basis of previous studies, I detailedly analyze and study various techniques of utilizing pre-stack data to get pre-stack attributes, and propose that pre-stack simultaneous inversion as an effective way of extracting pre-stack attributes accomplish better result in the real data application. By studying the reservoir properties and fluid response characteristics caused by a variety of pre-stack attributes, I propose and construct a new fluid identification factor and discuss its effectiveness. In addition, I develop a method of eliminating NMO stretch in angle domain which as supporting technology of pre-stack data processing plays a certain effect in improving the data resolution of Pre-stack gathers and the accuracy of pre-stack analysis.