Multi-wave Joint AVA Attributes Extraction And Hydrocarbon Prediction

For lithology and hydrocarbon prediction, the conventional AVA attributes analysis of PP wave is an important interpretation method. However, the prediction of hydrocarbon is usually ambiguous and the accuracy of the result is relatively low when only the PP wave data are used. So in this paper, we carry out a study on multi-wave joint AVA attributes analysis and hydrocarbon prediction.In order to improve the sensitivity to hydrocarbons of the commonly used attributes, we substitute the combination of the regularization parameter and shear wave impedance of the fluid indicator(Russell et al.,2003) by the lithology indictor(Sharma and Chopra, 2012), and obtain a new fluid indicator expressed by F?.So as to improve the accuracy of the AVA attributes extracted from the PP data, based on Aki-Richards’ reflection coefficient approximation, we derive a two-term linear reflection coefficient approximation in terms of fluid indicator( F?) and lithology indicator( E?). Then, we get the valid angle range of the proposed approximation by precision analysis. Then, we construct multi-wave joint AVA attributes equation based on the proposed approximation, and implement multi-wave joint two-term inversion by SVD method.At last, we examine the accuracy and the effectiveness of hydrocarbon indication of the proposed method by numerical and real data tests. The results show that the AVA attributes extracted from joint PP and PS waves are better than those extracted from only PP wave in the aspects of accuracy and effectiveness of hydrocarbon indication. So the proposed fluid indicators can be applied in the prediction of lithology and hydrocarbon prediction.