Nonlinear AVO inversion based on hybrid intelligent optimization algorithm
Fang Zhongyu1,2, Wang Liping3,4, Du Jiayuan5, Liang Lifeng2
1. College of Geophysics, Chengdu University of Technology, Chengdu, Sichuan 610059, China;
2. CNOOC EnerTech-Drilling & Production Co. Data Processing Co., Zhanjiang, Guangdong 524057, China;
3. Institute of Geophysics and Geomatics, China University of Geosciences(Wuhan), Wuhan, Hubei 430074, China;
4. Hubei Subsurface Multi-scale Imaging Key Laboratory, Wuhan, Hubei 430074, China;
5. Research Institute, Shenzhen Branch, CNOOC, Guangzhou, Guangdong 510240, China
Abstract：As the conventional prestack AVO inversion is dependent on the initial model and easily trapped into a local optimal solution,we propose a nonlinear AVO inversion based on the hybrid intelligent optimization algorithm.First we improve adaptively the conventional genetic algorithm.Then combining the improved genetic algorithm and particle swarm algorithm,we put forward a hybrid GA-PSO co-evolution algorithm.After that we apply the improved genetic algorithm,the particle swarm algorithm,and the GA-PSO co-evolution algorithm to model synthetic data.With the comparison of inverted P-wave velocity,shear wave velocity and density,the GA-PSO co-evolution algorithm shows better inversion result,better stability,and better anti-noise ability than the other two algorithms.In the end,AVO nonlinear inversion with the proposed algorithm is used to real data,and the results confirm its effectiveness and applicability.
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