基于瑞利波频散曲线和稀疏优化反演的速度建模

IF 1.2 4区数学 Q2 MATHEMATICS, APPLIED

Inverse Problems and Imaging Pub Date : 2021-01-01 DOI:10.3934/IPI.2021031

Yan Cui, Yanfei Wang

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引用次数: 1

摘要

本文研究了基于瑞利波频散曲线反演的横波速度模拟方法。我们首先讨论了正演模拟，并提出了一种三阶收敛速度的快速求根方法来获得瑞利波频散曲线。以瑞利波频散曲线为观测资料，考虑先验地质异常构造信息，建立了稀疏约束正则化模型，提出了求解S波速度的迭代求解方法。对理论模型和现场数据进行了实验验证。实验结果表明，该方法具有计算简便、计算效率高、模型表征精度高等特点。

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Velocity modeling based on Rayleigh wave dispersion curve and sparse optimization inversion

This paper studies the S wave velocity modeling based on the Rayleigh wave dispersion curve inversion. We first discuss the forward simulation, and present a fast root-finding method with cubic-order of convergence speed to obtain the Rayleigh wave dispersion curve. With the Rayleigh wave dispersion curve as the observation data, and considering the prior geological anomalies structural information, we establish a sparse constraint regularization model, and propose an iterative solution method to solve for the S wave velocity. Experimental tests are performed both on the theoretical models and on the field data. It indicates from the experimental results that our new inversion scheme possesses the characteristics of easy calculation, high computational efficiency and high precision for model characterization.

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来源期刊

Inverse Problems and Imaging 数学-物理：数学物理

CiteScore

2.50

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： Inverse Problems and Imaging publishes research articles of the highest quality that employ innovative mathematical and modeling techniques to study inverse and imaging problems arising in engineering and other sciences. Every published paper has a strong mathematical orientation employing methods from such areas as control theory, discrete mathematics, differential geometry, harmonic analysis, functional analysis, integral geometry, mathematical physics, numerical analysis, optimization, partial differential equations, and stochastic and statistical methods. The field of applications includes medical and other imaging, nondestructive testing, geophysical prospection and remote sensing as well as image analysis and image processing. This journal is committed to recording important new results in its field and will maintain the highest standards of innovation and quality. To be published in this journal, a paper must be correct, novel, nontrivial and of interest to a substantial number of researchers and readers.