基于正余弦算法的瑞利波频散曲线反演  

Inversion of the Rayleigh wave dispersion curves based on the sine-cosine algorithm

作　　者：付宇 艾寒冰 姚振岸 梅竹虚 苏可嘉 FU Yu;AI Han-Bing;YAO Zhen-An;MEI Zhu-Xu;SU Ke-Jia(Engineering Research Center for Seismic Disaster Prevention and Engineering Geological Disaster Detection of Jiangxi Province(East China University of Technology),Nanchang330013,China;School of Geophysics and Measurement-control Technology,East China University of Technology,Nanchang330013,China;School of Geophysics and Geomatics,China University of Geosciences(Wuhan),Wuhan430074,China;Research Institute No.270,CNNC,Nanchang330200,China)

机构地区：[1]江西省防震减灾与工程地质灾害探测工程研究中心,江西南昌330013 [2]东华理工大学地球物理与测控技术学院,江西南昌330013 [3]中国地质大学(武汉)地球物理与空间信息学院,湖北武汉430074 [4]核工业二七0研究所,江西南昌330200

出　　处：《物探与化探》2023年第6期1467-1478,共12页Geophysical and Geochemical Exploration

基　　金：江西省教育厅科学技术项目(GJJ200728);江西省自然科学基金项目(20212BAB211003);国家自然科学基金项目(42004113);江西省防震减灾与工程地质灾害探测工程研究中心开放基金项目(SDGD202006)。

摘　　要：瑞利波在工程勘察领域应用广泛,通过反演瑞利波频散曲线可有效地获取地层信息,但频散曲线反演中传统全局优化算法存在收敛速度慢、收敛精度低和易早熟的问题。对此,本文引入一种新的全局优化算法——正余弦算法(SCA)进行瑞利波频散曲线反演研究。SCA基于正余弦函数数学性质,应用多个随机参数和自适应变量调整寻优过程中的探索和开发能力,在获得高精度解的同时还保证了收敛速度以及稳定性。首先利用4个不含噪声模型验证了SCA用于频散曲线反演的可行性;随后往模型中加入15%的随机噪声说明了SCA具有较强的抗干扰能力;接着将SCA与粒子群算法(PSO)进行对比,证明了SCA反演频散曲线能得到高精度和高稳定性的解;最后用冰岛Arnarb?lidi和美国怀俄明地区的地震数据检验SCA处理实际数据的能力。理论模型试算与实测资料分析的结果表明,SCA具有快速、高精度、稳定、实用性强的特点,可有效地应用于瑞利波频散曲线的定量解释。Rayleigh wave is widely used in engineering investigation and surveys.The inversion of its dispersion curves allows for effec-tively obtaining stratigraphic information.However,conventional global optimization algorithms in the dispersion curve inversion have a slow convergence rate and low convergence precision and are prone to prematurity.Therefore,this study introduced a novel global opti-mization algorithm—the sine cosine algorithm(SCA)—to solve the problems mentioned above.Based on the mathematical properties of sine and cosine functions,the SCA can adjust the exploration and development capabilities during the optimization using multiple ran-dom parameters and adaptive variables.As a result,it can ensure a high convergence rate and great stability while obtaining high-accu-racy solutions.First,the feasibility of the SCA for the dispersion curve inversion was verified using four noise-free models.Then,the strong anti-interference ability of the SCA was proved by adding 15%of random noise to the models.Afterward,it was verified that SCA can yield high-precision,high-stability solutions in the dispersion curve inversion by comparison with the particle swarm optimization(PSO)approach.Finally,the practicability of the SCA was confirmed using seismic data from Arnarbælidi in Iceland and Wyoming in the USA.As indicated by the calculation results of theoretical models and the analysis of measured data,the SCA has a high processing speed,precision,stability,and practicability and thus allows for effective quantitative interpretation of the Rayleigh wave dispersion curves.

关 键 词：瑞利波 频散曲线反演 全局优化 正余弦算法 

分 类 号：P631.4[天文地球—地质矿产勘探]