Quantitative evaluation of gas hydrate reservoir by AVO attributes analysis based on the Brekhovskikh equation

作     者：Yao Wang Yan-Fei Wang 

作者机构：Key Laboratory of Petroleum Resources ResearchInstitute of Geology and GeophysicsChinese Academy of SciencesBeijing100029China University of Chinese Academy of SciencesBeijing100049China Innovation Academy for Earth ScienceChinese Academy of SciencesBeijing100029China 

出 版 物：《Petroleum Science》 (石油科学（英文版）)

年 卷 期：2023年第20卷第4期

页      面：2045-2059页

核心收录：

学科分类：0820[工学-石油与天然气工程] 0817[工学-化学工程与技术] 08[工学] 0818[工学-地质资源与地质工程] 082002[工学-油气田开发工程] 

基　　金：The research is funded by the National Natural Science Foundation of China(No.12171455) the Original Innovation Research Program of the Chinese Academy of Sciences(CAS)under grant number ZDBS-LY-DQC003 the Key Research Programs IGGCAS-2019031 

主　　题：Natural gas hydrate Brekhovskikh equation AVO attributes Random forest 

摘      要：AVO (Amplitude variation with offset) technology is widely used in gas hydrate research. BSR (Bottom simulating reflector), caused by the huge difference in wave impedance between the hydrate reservoir and the underlying free gas reservoir, is the bottom boundary mark of the hydrate reservoir. Analyzing the AVO attributes of BSR can evaluate hydrate reservoirs. However, the Zoeppritz equation which is the theoretical basis of conventional AVO technology has inherent problems: the Zoeppritz equation does not consider the influence of thin layer thickness on reflection coefficients;the approximation of the Zoeppritz equation assumes that the difference of wave impedance between the two sides of the interface is small. These assumptions are not consistent with the occurrence characteristics of natural gas hydrate. The Brekhovskikh equation, which is more suitable for thin-layer reflection coefficient calculation, is used as the theoretical basis for AVO analysis. The reflection coefficients calculated by the Brekhovskikh equation are complex numbers with phase angles. Therefore, attributes of the reflection coefficient and its phase angle changing with offset are used to analyze the hydrate reservoir s porosity, saturation, and thickness. Finally, the random forest algorithm is used to predict the reservoir porosity, hydrate saturation, and thickness of the hydrate reservoir. In the synthetic data, the inversion results based on the four attributes of the Brekhovskikh equation are better than the conventional inversion results based on the two attributes of Zoeppritz, and the thickness can be accurately predicted. The proposed method also achieves good results in the application of Blake Ridge data. According to the method proposed in this paper, the hydrate reservoir in the area has a high porosity (more than 50%), and a medium saturation (between 10% and 20%). The thickness is mainly between 200m and 300m. It is consistent with the previous results obtained by veloci