The Study On Methods Of Pre-stack Inversion And Fluid Discrimination In Northeast Region Of Sichuan

Carbonate rocks are rich in oil and gas resources, and carbonate reservoir has played an important role in the global oil and gas exploration. The northeast region of Sichuan is typical of marine carbonate deposition, which is a gas-enrichment area of China. The famous Puguang gas field is located in this region. However, the surface in northeastern Sichuan is undulating, and the gas resources are buried deeply under the earth. As the carbonate rock fractures, and strongly lack of homogeneity, this made the reservoirfluid a big problem for seismic exploration in the northeast region of Sichuan. Based on the rock physical analysis of carbonate rocks, and the summaries of the law, this article studied the pre-stack seismic data inversion method with logging, geological information. Meanwhile we achieved carbonate reservoir fluid discrimination in by improving the optimization algorithm and the inversion of elastic parameters of the extraction methods.Pre-stack seismic data has incomparable advantages. It has plenty of angle information which is needed by the AVO inversion and elastic impedance inversion. The seismic data can effectively reflect the reef Phase structure characteristics. In that way, we can effectively ensure to start the pre-stack seismic inversion and the fluid discrimination. By combining the Northeast geology, well logging and rock physics data, This paper is a study in the following 3 points: (1) Northeast multi-well petro-physical characteristics of the data analysis, the rock is suitable for the physical experience of the area formula lithological parameters of the fluid through the intersection of the sensitivity obtained for the parameters of the zone of fluid identification. (2) Using the Powell algorithm to improve and enhance the prestack AVO inversion of computational efficiency and accuracy, and make up for some lack of missing wave data. (3) The pre-stack elastic impedance inversion and the improved elasticity parameter extraction methods are carried out to improve the inversion results of the resolution and precision of fluid identification.