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基于贝叶斯原理的PP波和PS波AVO联合反演方法研究(英文)
引用本文:胡国庆,刘洋,魏修成,陈天胜. 基于贝叶斯原理的PP波和PS波AVO联合反演方法研究(英文)[J]. 应用地球物理, 2011, 8(4): 293-302. DOI: 10.1007/s11770-010-0306-0
作者姓名:胡国庆  刘洋  魏修成  陈天胜
作者单位:中国石油大学(北京)油气资源与探测国家重点实验室;中国石油大学(北京)CNPC物探重点实验室;中国石化石油勘探开发研究院
基金项目:supported by the China Important National Science & Technology Specific Projects (Grant No. 2011ZX05019-008);the National Natural Science Foundation of China (Grant No. 40839901)
摘    要:基于Aki-Richards公式和贝叶斯原理,本文发展了利用叠前PP波和PS波资料联合反演P波速度比、S波速度比和密度比的方法。该方法假设参数之间满足正态分布,引入参数协方差矩阵来描述反演参数之间的相关性以提高反演过程的稳定性,并同时使反演的参数序列服从Cauchy分布,引入矩阵Q来描述参数序列的稀疏性以提高反演结果的分辨率。采用本文提出的方法对模型数据和实际多波资料进行反演,结果表明:本文方法正确有效;与传统的单一PP波反演相比,PP波和PS波AVO联合反演具有稳定性更好和反演精度更高等优点。

关 键 词:PP波  PS波  联合反演  贝叶斯原理

Joint PP and PS AVO inversion based on Bayes theorem
Guo-Qing Hu,Yang Liu,Xiu-Cheng Wei,Tian-Sheng Chen. Joint PP and PS AVO inversion based on Bayes theorem[J]. Applied Geophysics, 2011, 8(4): 293-302. DOI: 10.1007/s11770-010-0306-0
Authors:Guo-Qing Hu  Yang Liu  Xiu-Cheng Wei  Tian-Sheng Chen
Affiliation:1. State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing, 102249, China
2. CNPC Key Laboratory of Geophysical Exploration, China University of Petroleum, Beijing, 102249, China
3. Exploration & Production Research Institute, SINOPEC, Beijing, 100083, China
Abstract:Based on the Aki-Richards approximate equations for reflection coefficients and Bayes theorem, we developed an inversion method to estimate P- and S-wave velocity contrasts and density contrast from combined PP and PS data. This method assumes that the parameters satisfy a normal distribution and introduces the covariance matrix to describe the degree of correlation between the parameters and thus to improve the inversion stability. Then, we suppose that the parameter sequence is subject to the Cauchy distribution and employs another matrix Q to describe the parameter sequence sparseness to improve the inversion result resolution. Tests on both synthetic and real multi-component data prove that this method is valid, efficient, more stable, and more accurate compared to methods using PP data only.
Keywords:PP wave  converted PS wave  joint PP and PS inversion  Bayes theorem
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