基于遗传优化算法的矿区地下结构识别  

Underground Structure Identification in Mining Areas Based on Genetic Algorithm

作　　者：毕升博 姚振岸 卜凯旭 朱毅 詹晨昊 BI Shengbo;YAO Zhenan;BU Kaixu;ZHU Yi;ZHAN Chenhao(East China University of Technology,School of Geophysics and Measurement-Control Technology,330013,Nanchang,PRC)

机构地区：[1]东华理工大学地球物理与测控技术学院,南昌330013

出　　处：《江西科学》2024年第6期1183-1189,1270,共8页Jiangxi Science

基　　金：江西省大学生创新创业科研项目(S202310405011,S202310405036)。

摘　　要：为了研究了瑞雷面波勘探技术在地质结构分析中的应用,将具有模拟自然选择和遗传机制优势的遗传算法(GA)为实验算法,重点探讨了其在频散曲线反演中的应用。通过瑞雷波在地表或地层分界面传播的特性,以及在层状介质中的频散特性构建理论地质构造平层模型,验证了GA算法在反演地下结构时的有效性和稳定性。结果表明,GA算法能够准确地反演出地下速度结构,尤其是在浅层地区。此外,还利用实测数据,采用微动探测方法结合GA算法对矿区地下结构进行了探测和分析,为矿区提供了下一步勘探与治理的方向。研究证实了GA算法在解决复杂地质结构反演问题方面的潜力,并为进一步识别地下岩性结构提供了新的方法。To investigate the application of Rayleigh wave exploration technology in geological structure analysis,the authors utilized the Genetic Alg orithm(GA),which simulates natural selection and genetic mechanisms,as the experimental alg orithm.This study primarily focuses on its application in the inversion of dispersion curves.By leveraging the characteristics of Rayleigh waves propagating along the surface or layer interfaces and their dispersion properties in stratified media,a theoretical geological structure layered model was constructed to verify the effectiveness and stability of the GA in inverting underground structures.The results demonstrate that the GA can accurately invert the underground velocity structure,particularly in shallow regions.Additionally,this paper utilizes actual measured data and combines the microtremor exploration method with the GA to probe and analyze the underground structure of the mining area,providing direction for future exploration and management of the area.The study confirms the potential of the GA in solving complex geological structure inversion problems and offers a new method for further identifying underground lithological structures.

关 键 词：遗传算法 面波勘探 地震正反演 地下速度结构 

分 类 号：P315[天文地球—地震学]