An Exact Zoeppritz Based Prestack Inversion Using Whale Optimization Particle Filter Algorithm Under Bayesian Framework

被引:8
作者
Tang, Jing [1 ]
Li, Peng [1 ]
Huang, Xuri [2 ]
Lai, Qiang [3 ]
Wang, Ding [4 ]
机构
[1] Southwest Petr Univ, Sch Geosci & Technol, Chengdu, Peoples R China
[2] Southwest Petr Univ, Sch Geosci & Technol, State Key Lab Oil & Gas Reservoir Geol & Exploitat, Chengdu, Peoples R China
[3] PetroChina Southwest Oil & Gasfield Co, Chengdu, Peoples R China
[4] Shaoxing Univ, Key Lab Rock Mech & Geohazards Zhejiang Prov, Shaoxing, Peoples R China
来源
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 2023年 / 61卷
基金
中国国家自然科学基金;
关键词
Mathematical models; Whale optimization algorithms; Bayes methods; Whales; Particle filters; Fluids; Filtering; Amplitude versus offset (AVO); exact Zoeppritz equation; particle filter (PF); whale optimization particle filter (WOPF) algorithm; WAVE REFLECTION COEFFICIENTS; SEISMIC INVERSION; AVO INVERSION; PREDICTION;
D O I
10.1109/TGRS.2022.3223060
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
Conventional amplitude versus offset (AVO) inversion methods are mainly based on various Zoeppritz approximations. The assumptions of small contrast and linear relationship lead to the most inversion methods being difficult to have high inversion accuracy. In this article, the exact Zoeppritz equation is used to establish the prestack inversion method under the Bayesian framework. It integrates multisource information to generate posterior distributions of P-, S-wave velocity and density. In the Bayesian theory, the prior model works as the regularization term which has a strong effect on the inversion results. The strategy to obtain a relatively accurate prior model can improve the inversion accuracy. Therefore, an exact Zoeppritz equation based nonlinear AVO inversion algorithm combing whale optimization particle filtering (WOPF) is proposed. The WOPF method can generate a relatively stable and accurate initial model for the Bayesian prestack inversion. We validate the new method through two synthetic models and field data. Comparisons are made with the conventional linear and nonlinear AVO inversion methods. The results show that the proposed method can provide much more accurate inverted elastic parameters in different geological conditions.
引用
收藏
页数:10
相关论文
共 31 条
[1]   High-resolution three-term AVO inversion by means of a Trivariate Cauchy probability distribution [J].
Alemie, Wubshet ;
Sacchi, Mauricio D. .
GEOPHYSICS, 2011, 76 (03) :R43-R55
[2]   Bayesian linearized AVO inversion [J].
Buland, A ;
Omre, H .
GEOPHYSICS, 2003, 68 (01) :185-198
[3]  
Chen Z., 2017, ACTA PHYS SIN-CH ED, V66, P47
[4]  
Downton J.E., 2005, Seismic Parameter Estimation from AVO Inversion
[5]   Bayesian Seismic AVO Inversion Using a Laterally Coupled Multimodal Prior Model [J].
Forberg, Ole Bernhard ;
Kjosnes, Oyvind ;
Omre, Henning .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60
[6]   Interpretation of AVO anomalies [J].
Foster, Douglas J. ;
Keys, Robert G. ;
Lane, F. David .
GEOPHYSICS, 2010, 75 (05) :A3-A13
[7]   NOVEL-APPROACH TO NONLINEAR NON-GAUSSIAN BAYESIAN STATE ESTIMATION [J].
GORDON, NJ ;
SALMOND, DJ ;
SMITH, AFM .
IEE PROCEEDINGS-F RADAR AND SIGNAL PROCESSING, 1993, 140 (02) :107-113
[8]  
Guo Q, 2021, GEOPHYSICS, V86, pR895, DOI [10.1190/geo2021-0017.1, 10.1190/GEO2021-0017.1]
[9]   Seismic rock physics inversion with varying pore aspect ratio in tight sandstone reservoirs [J].
Guo, Qiang ;
Ba, Jing ;
Luo, Cong ;
Pang, Mengqiang .
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING, 2021, 207
[10]   Prestack Seismic Inversion With Data-Driven MRF-Based Regularization [J].
Guo, Qiang ;
Ba, Jing ;
Luo, Cong .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2021, 59 (08) :7122-7136