石油地球物理勘探2019，Vol.54Issue(2)：288-301,前插2,15.DOI:10.13810/j.cnki.issn.1000-7210.2019.02.007
蚱蜢算法在瑞雷波频散曲线反演中的应用
Rayleigh wave dispersion inversion based on grasshopper optimization algorithm
摘要
Abstract
As a new algorithm,the grasshopper optimization algorithm(GOA )belongs to swarm intelligent algorithms. It is inspired by the unique foraging behavior of grasshoppers at different stages.The movement of any grasshopper will be impacted by all the other grasshopper, which ensure the accuracy of convergence.In this paper,GOA is applied to invert surface-wave phase velocities. Using synthetic and real Rayleigh wave data, we examine the effectiveness and applicability of the GOA scheme in deducing an S-wave velocity profile for near-surface applications.The objective function in the proposed algorithm is proved to be able to rapidly converge to the global optimization solution.Another advantage of the proposed algorithm is a wide probability distribution of model parameters,which means this algorithm can define the scope of true-value and find the global minimum even in an extensive search space to guarantee the reliability of inversion results.关键词
蚱蜢算法/群智能/瑞雷波/频散曲线/非线性反演Key words
grasshopper optimization algorithm(GOA)/swarm intelligence/Rayleigh wave/dispersion curve/nonlinear inversion分类
天文与地球科学引用本文复制引用
于东凯,宋先海,张学强,赵素涛,蔡伟..蚱蜢算法在瑞雷波频散曲线反演中的应用[J].石油地球物理勘探,2019,54(2):288-301,前插2,15.基金项目
本项研究受国家自然科学基金项目"起伏地表二维粘弹复杂介质瑞雷波全波形反演研究"(41874150)和"起伏地表粘弹复杂介质三维多分量瑞雷波传播特性研究"(41574114)联合资助. （41874150）
