应用闪电连接过程优化算法反演多阶瑞雷波频散曲线

doi:10.13810/j.cnki.issn.1000-7210.2023.04.008

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摘要在瑞雷波勘探中，频散曲线反演是获取地下地层信息的关键，具有多参数、多极值特征。传统的全局优化算法，如粒子群（PSO）算法、遗传算法（GA）等，进行频散曲线反演时存在收敛速度慢、求解精度低等问题。为此，将一种新颖的全局优化算法——闪电连接过程优化（Lightning Attachment Procedure Optimization，LAPO）算法用于频散曲线反演。LAPO算法受自然界中闪电下行先导和上迎先导连接过程的启发所提出，通过模拟自然界中闪电形成过程寻求最优解。该算法全局搜索和局部开发能力都强，无需进行参数调整。使用理论地质模型和实际数据进行测试，结果表明：与PSO算法相比，LAPO算法具有收敛速度快、求解精度高、算法性能稳定的特点； LAPO算法不仅适用于基阶频散曲线反演，而且适用于多阶频散曲线反演，是瑞雷波频散曲线定量解释的有效工具。

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	付宇
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关键词 ：瑞雷波, 频散曲线反演, 多阶, 全局优化, 闪电连接过程优化算法

Abstract：In Rayleigh wave exploration, inversion of picked dispersion curves is the key to retrieving subsurface stratigraphic information, which is characterized by multiple parameters and optimal values. Traditional global optimization methods such as particle swarm optimization(PSO) algorithm and genetic algorithm(GA) feature slow convergence speed and low precision. To this end, this paper adopts a novel global optimization algorithm, lightning attachment procedure optimization(LAPO) for dispersion curve inversion. The LAPO algorithm is inspired by the natural lightning formation process involving the process of connecting downward and upward leader movements. This algorithm can find the optimal solution by simulating the lightning formation process in nature and has strong global search and local exploitation abilities without parameter tuning. Tests carried out through the theoretical geological model and actual data show that compared with PSO, LAPO yields faster convergence speed, higher solution accuracy, and more stable performance. Additionally, it can be applied to the inversion of both fundamental and multimode dispersion curves, and is a valuable tool for the quantitative interpretation of Rayleigh dispersion curves.

Key words： Rayleigh wave dispersion curve inversion multi-mode global optimization lightning attachment procedure optimization(LAPO)

收稿日期: 2022-07-14

PACS:

P631

基金资助:本项研究受国家自然基金项目“黏弹各向异性介质复杂震源机制解析与微地震响应高精度正演”（42004113）、江西省自然科学基金项目“复杂介质微地震响应无网格高精正演与震源机制解析”（20212BAB211003）、“基于人工智能的江西地区天然地震和非天然地震事件识别方法研究”（2022AB213047）、江西省大学生创新创业项目“探地雷达在植物根干探测中的应用研究”（S202210405012）、“基于机器学习的瑞雷面波反演方法研究”（S202210405013）、“南昌市地下空间微动探测方法研究”（S202210405016）和东华理工大学研究生创新基金项目“利用地脉动资料研究萍乡矿区地壳浅层三维横波速度结构”（YC2021-S644）联合资助。

通讯作者: 姚振岸,江西省南昌市经开区广兰大道418号东华理工大学地球物理与测控技术学院,330013。Email:an6428060@163.com E-mail: an6428060@163.com

作者简介: 付宇硕士研究生,1998年生;2020年毕业于东华理工大学长江学院,获勘查技术与工程专业学士学位;现在东华理工大学攻读地球物理学专业硕士学位,研究方向为近地表面波勘探。

引用本文:

付宇, 艾寒冰, 姚振岸, 李红星, 田宵, 张杏棉. 应用闪电连接过程优化算法反演多阶瑞雷波频散曲线[J]. 石油地球物理勘探, 2023, 58(4): 830-838. FU Yu, AI Hanbing, YAO Zhen'an, LI Hongxing, TIAN Xiao, ZHANG Xingmian. Inversion of multi-mode Rayleigh wave dispersion curves based on lightning attachment procedure optimization. Oil Geophysical Prospecting, 2023, 58(4): 830-838.

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