利用粒子群优化方法结合GPR和p波地震走时的全球反演

J. Tronicke, H. Paasche, Urs Boniger
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引用次数: 5

摘要

粒子群算法(PSO)是一种受鸟类和鱼类社会行为启发的较新的全局优化方法。尽管该方法在不同的优化问题中具有优异的收敛速度,但很少用于地球物理反演。在此,我们提出了一种基于pso的反演策略,用于联合反演同位井间实验的探地雷达和纵波地震走时。通过一个合成数据示例,我们展示了这种方法的潜力。将我们的结果与输入模型以及使用标准线性化反演方法分别反演数据得到的速度模型进行比较,说明了使用有效的全局优化方法解决此类联合反演问题的好处。这些包括对不确定性、非唯一性和解决问题的直接评估,以及改进和更客观解释的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Join global inversion of GPR and P-wave seismic traveltimes using particle swarm optimization
Particle swarm optimization (PSO) is a relatively new global optimization approach inspired by the social behavior of birds and fishes. Although this approach has proven to provide excellent convergence rates in different optimization problems, it has seldom been used in geophysical inversion. Here, we propose a PSO-based inversion strategy to jointly invert GPR and P-wave seismic traveltimes from co-located crosshole experiments. Using a synthetic data example, we demonstrate the potential of our approach. Comparing our results to the input models as well as to velocity models found by separately inverting the data using a standard linearized inversion approach, illustrates the benefits of using an efficient global optimization approach for such a joint inversion problem. These include a straightforward appraisal of uncertainty, non-uniqueness, and resolution issues as well as the possibility of an improved and more objective interpretation.
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