Prestack global iteration geostatistical inversion method based on metropolis sampling algorithm

被引：1
|
作者：
Zhao Chen [1 ]
Zhang GuangZhi [1 ,2 ]
Zhang JiaJia [1 ,2 ]
Xi Cheng [3 ]
Xiao YaNan [1 ]
机构：
[1] China Univ Petr East China, Qingdao 266580, Peoples R China
[2] Qingdao Natl Lab Marine Sci & Technol, Lab Marine Mineral Resources, Qingdao 266071, Peoples R China
[3] PetroChina Southwest Oil & Gas Field Co, Res Inst Explorat & Dev, Chengdu 610041, Peoples R China
来源：
CHINESE JOURNAL OF GEOPHYSICS-CHINESE EDITION | 2020年 / 63卷 / 08期
关键词：
Geostatistical inversion; Direct sequential simulation; Optimized local correlation coefficient; Prestack AVO inversion; Metropolis sampling algorithm; STOCHASTIC INVERSION; PARAMETERS; SIMULATION;
D O I：
10.6038/cjg2020M0674
中图分类号：
P3 [地球物理学]; P59 [地球化学];
学科分类号：
0708 ; 070902 ;
摘要：
The prestack geostatistics inversion method combining stochastic simulation with prestack seismic inversion can invert for various elastic properties and improve the resolution of inversion results. The direct sequential co-simulation method based on the joint probability distribution can simulate data in the original data domain without Gaussian transformation, which expands the application scope of geostatistical inversion. In addition, the application of the joint probability distribution ensures the correlation between the inverted properties and improve the accuracy of the inversion. In this paper, combining the metropolis sampling algorithm with the direct sequential co-simulation method, the global iteration geostatistical inversion method based on Metropolis sampling algorithm is proposed by referring the global stochastic inversion strategy. In order to improve the stability of inversion, we modified the calculation formula of local correlation coefficient, and proposed a new calculation formula of optimized local correlation coefficient based on the objective function. Model testing and application to actual data demonstrate that this method works well in prestack inversion.
引用
收藏
页码：3116 / 3130
页数：15
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