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Particle swarm optimization and its application to seismic inversion of igneous rocks 被引量:3
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作者 Yang Haijun Xu Yongzhong +6 位作者 Peng Gengxin Yu Guiping Chen Meng Duan Wensheng Zhu Yongfeng Cui Yongfu Wang Xingjun 《International Journal of Mining Science and Technology》 SCIE EI CSCD 2017年第2期349-357,共9页
In order to improve the fine structure inversion ability of igneous rocks for the exploration of underlying strata, based on particle swarm optimization(PSO), we have developed a method for seismic wave impedance inve... In order to improve the fine structure inversion ability of igneous rocks for the exploration of underlying strata, based on particle swarm optimization(PSO), we have developed a method for seismic wave impedance inversion. Through numerical simulation, we tested the effects of different algorithm parameters and different model parameterization methods on PSO wave impedance inversion, and analyzed the characteristics of PSO method. Under the conclusions drawn from numerical simulation, we propose the scheme of combining a cross-moving strategy based on a divided block model and high-frequency filtering technology for PSO inversion. By analyzing the inversion results of a wedge model of a pitchout coal seam and a coal coking model with igneous rock intrusion, we discuss the vertical and horizontal resolution, stability and reliability of PSO inversion. Based on the actual seismic and logging data from an igneous area, by taking a seismic profile through wells as an example, we discuss the characteristics of three inversion methods, including model-based wave impedance inversion, multi-attribute seismic inversion based on probabilistic neural network(PNN) and wave impedance inversion based on PSO.And we draw the conclusion that the inversion based on PSO method has a better result for this igneous area. 展开更多
关键词 particle swarm optimization Seismic inversion Igneous rocks Probabilistic neutral network Model-based inversion
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