Non-linear AVO inversion based on PSO-LSSVM

被引：0
|
作者：
Xie W. [1 ]
Wang Y. [1 ]
Liu J. [2 ]
Su J. [3 ]
Mao Q. [1 ]
He R. [1 ]
机构：
[1] School of Geophysics and Information Technology, China University of Geosciences, Beijing
[2] Research Institute of Petroleum Exploration & Development, Huabei Oilfield Company, PetroChina, Renqiu, 062550, Hebei
[3] Exploration Company, SINOPEC, Chengdu, 610041, Sichuan
来源：
Shiyou Diqiu Wuli Kantan/Oil Geophysical Prospecting | 2016年 / 51卷 / 06期
关键词：
Generalized linear AVO inversion; Least squares support vector machine (LSSVM); Non-linear AVO inversion; Particle swarm optimization (PSO);
D O I：
10.13810/j.cnki.issn.1000-7210.2016.06.019
中图分类号：
学科分类号：
摘要：
We propose in this paper a new non-linear inversion method to solve non-linear AVO inversion problems, which is based on least square support vector machine (LSSVM) and particle swarm optimization (PSO). And LSSVM parameters are optimized by PSO. Firstly angle gathers obtained with Zoeppritz's equations are partially stacked after normal moveout (NMO) correction. Then a LSSVM non-linear model is established in order to define the relationship between amplitude and elastic parameter. Finally the elastic parameters are calculated according to this non-linear model. Both synthetic data and field data are inverted by the proposed non-linear inversion method. The inversion results show that the proposed method can overcome the problems in generalized linear AVO inversion due to far offset or violent variation of elastic parameters. This method can also directly extract the elastic parameters from seismic records with high speed and good stability. © 2016, Editorial Department OIL GEOPHYSICAL PROSPECTING. All right reserved.
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页码：1187 / 1194
页数：7
相关论文
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