[an error occurred while processing this directive] Global Geology 2019, 22(3) 188-198 DOI:   10.3969/j.issn.1673-9736.2019.03.06  ISSN: 1673-9736 CN: 22-1371/P
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genetic algorithm
adaptive probability
regional equilibrium
seismic inversion
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PubMed
Pre-stack seismic waveform inversion based on adaptive genetic algorithm
LIU Sixiu, WANG Deli, HU Bin
College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China
ժҪ�� Pre-stack waveform inversion, by inverting seismic information, can estimate subsurface elastic properties for reservoir characterization, thus effectively guiding exploration. In recent years, nonlinear inversion methods, such as standard genetic algorithm, have been extensively adopted in seismic inversion due to its simplicity, versatility, and robustness. However, standard genetic algorithms have some shortcomings, such as slow convergence rate and easiness to fall into local optimum. In order to overcome these problems, the authors present a new adaptive genetic algorithm for seismic inversion, in which the selection adopts regional equilibrium and elite retention strategies are adopted, and adaptive operators are used in the crossover and mutation to implement local search. After applying this method to pre-stack seismic data, it is found that higher quality inversion results can be achieved within reasonable running time.
�ؼ����� genetic algorithm   adaptive probability   regional equilibrium   seismic inversion  
Pre-stack seismic waveform inversion based on adaptive genetic algorithm
LIU Sixiu, WANG Deli, HU Bin
College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China
Abstract: Pre-stack waveform inversion, by inverting seismic information, can estimate subsurface elastic properties for reservoir characterization, thus effectively guiding exploration. In recent years, nonlinear inversion methods, such as standard genetic algorithm, have been extensively adopted in seismic inversion due to its simplicity, versatility, and robustness. However, standard genetic algorithms have some shortcomings, such as slow convergence rate and easiness to fall into local optimum. In order to overcome these problems, the authors present a new adaptive genetic algorithm for seismic inversion, in which the selection adopts regional equilibrium and elite retention strategies are adopted, and adaptive operators are used in the crossover and mutation to implement local search. After applying this method to pre-stack seismic data, it is found that higher quality inversion results can be achieved within reasonable running time.
Keywords: genetic algorithm   adaptive probability   regional equilibrium   seismic inversion  
�ո����� 2019-06-05 �޻����� 2019-06-30 ����淢������  
DOI: 10.3969/j.issn.1673-9736.2019.03.06
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Supported by the Major Projects of the National Science and Technology of China (No. 2016ZX05026-002-003) and National Natural Science Foundation of China (No. 41374108).

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