S-Wave Prediction And Its Application Of AVO Prestack Inversion

After the seismic data is processed by many times, the effective reflection wave is enhanced and reduces the interference wave effectively which improves the quality of data. Compared to pre-stack data, some information was lost due to its own limitations, so this process will affect the accuracy of the forecast. In the pre-stack gathers, the variation law of the amplitude and the angle of incidence is preserved completely. Therefore, the AVO inversion of pre-stack data can get the parameters of vertical and horizontal wave velocity, density, and so on, through the combination of various parameters can get more information about the characteristics of the underground lithology and physical properties. The Zoeppritz equation, which is the basis of AVO inversion theory, is too complicated. We have to simplify the equation in order to used in real environment. Many scholars have simplified the Zoeppritz equation according to different assumptions and objectives. The problem of AVO inversion is ill posed (Chen Jianjiang,2007). By combining with well logging data, it can effectively increase the reliability of the inversion. Different from the post-stack inversion, the shear wave plays an important role in pre-stack inversion. Shear wave logging is difficult and the cost is high, and it is often lack of shear wave in conventional well logging. The fact is, the old area lack of shear wave data, the new area is often has only one or very little wells with shear wave data. This situation makes the application of the pre-stack AVO inversion limited. Predict the shear wave can be through the actual data of existing or laboratory measurement data fitting S-wave velocity use data like density, P-wave velocity and mud content parameters, then calculate for shear wave of unknown target area. Based on the direct fitting of the actual data, the calculation is simple, but the accuracy is poor. When the geological structure of the source area and the target area is not the same, it will produce a large error which we cannot ignore. Another commonly used method is based on the rock physics model. By means of the equivalent medium theory and the self compatibility theory, the rock physical model is established to describe the characteristics of the subsurface structure. Xu-white model for the classification of pores is muddy pore and sandy pore which use sandy pore aspect ratio and mud aspect to describe respectively, through the theory of K-T measure modulus of rock matrix and relation of dry rock modulus can make use of Gassmann theory of rock under the condition of the real fluid shear wave velocity is obtained and achieved good application effect in the sand shale formation with right parameter setting. By improving the method of pore division, theXu-White model has achieved good results in carbonate rocks and reefs. Because the geometry of the underground rock is difficult to understand directly, the definition of the aspect ratio of the pore is clear, but it is difficult to directly measure, which directly restricts the prediction accuracy of the Xu-White model.On the basis of previous studies, this paper introduces some basic theories of rock physics briefly, focusing on the space average model and the differential equivalent medium model. The analysis of various factors include pore fluid to influence on the wave and fluid mechanics model of the Gassmann equation’s assumptions, its common form and replacement process has been made detailed description. Three types of commonly used empirical formula (longitudinal and transverse waves, velocity and density, velocity and porosity) are summarized.In the traditional Xu-White model, the influence factors were analyzed, including the relative change of pore aspect ratio and the ratio of the pore aspect ratio. The influence of the vertical and horizontal wave velocity was analyzed in two aspects. As a wave as constraint, above the rock physics model constrained inversion parameters based on the range, to pore aspect ratio, the empirical relationship between the shale content, porosity as a guide, the introduction of join the idea of simulated annealing particle swarm optimization algorithm for inversion method, the shear wave velocity as a target of inversion. The predicted shear wave and the conventional method are compared with the AVO inversion results of the actual shear wave. It is proved that the high precision shear wave prediction method provides a reliable basis for the accurate prediction of reservoir.