Prediction of fracture gas bearing based on frequency-dependent AVAZ inversion in orthotropic medium
CHEN Tianjie1, CHENG Bingjie1, XU Tianji2,3, QIAN Zhongping4, ZOU Zhen4
1. Key Laboratory of Earth Exploitation and Information Technology, Ministry of Education, Chengdu University of Technology, Chengdu, Sichuan 610059, China; 2. School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China; 3. Yangtze Delta Region Institute of University of Electronic Science and Technology of China(Huzhou), Huzhou, Zhejiang 313099, China; 4. National Engineering Research Center for Oil and Gas Exploration Computer Software, Beijing 100088, China
Abstract：The frequency-dependent AVO inversion method （FDAVO） can extract fluid-related anomaly information, but it is difficult to apply to fractured reservoirs because it fails to consider the effect of anisotropy in real reservoirs. In addition, the anisotropy is often frequency-dependent, which facilitates the identification of effective fractures using OVT domain pre-stack seismic data. Therefore, a frequency-dependent AVAZ （OA-FDAVAZ） inversion method for gas content prediction based on orthotropic （OA） media is proposed. Firstly, based on the numerical simulation of the Chapman model, the variation characteristics of elastic parameters with frequency and incidence angle are analyzed. Then, the objective equation of OA-FDAVAZ inversion is derived based on the approximation of the P-wave reflection coefficient of OA media, and a new dispersion attribute Iani is constructed. Finally, the least square method is used to invert the OA dispersion properties. The model test results show that the OA dispersion property of the gas-bearing fractured layer is obviously stronger than that of the water-bearing fractured layer, while the anisotropic layer without cracks has a weak dispersion response, which verifies the sensitivity of the proposed dispersion property to fluid. The application results of OVT domain pre-stack seismic data show that the prediction results of the OA dispersion attribute are in good agreement with the drilling results. Compared with traditional methods, the proposed method is less affected by background interference and can accurately characterize the spatial distribution characteristics of gas bearing in fractures in reservoirs.
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