Near-surface velocity inversion from Rayleigh wave dispersion curves based on a differential evolution simulated annealing algorithm

Yaojun Wang , Hua Wang , Xijun Wu , Keyu Chen , Sheng Liu , Xiaodong Deng
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引用次数: 2

Abstract

The utilization of urban underground space in a smart city requires an accurate understanding of the underground structure. As an effective technique, Rayleigh wave exploration can accurately obtain information on the subsurface. In particular, Rayleigh wave dispersion curves can be used to determine the near-surface shear-wave velocity structure. This is a typical multiparameter, high-dimensional nonlinear inverse problem because the velocities and thickness of each layer must be inverted simultaneously. Nonlinear methods such as simulated annealing (SA) are commonly used to solve this inverse problem. However, SA controls the iterative process though temperature rather than the error, and the search direction is random; hence, SA always falls into a local optimum when the temperature setting is inaccurate. Specifically, for the inversion of Rayleigh wave dispersion curves, the inversion accuracy will decrease with an increasing number of layers due to the greater number of inversion parameters and large dimension. To solve the above problems, we convert the multiparameter, high-dimensional inverse problem into multiple low-dimensional optimizations to improve the algorithm accuracy by incorporating the principle of block coordinate descent (BCD) into SA. Then, we convert the temperature control conditions in the original SA method into error control conditions. At the same time, we introduce the differential evolution (DE) method to ensure that the iterative error steadily decreases by correcting the iterative error direction in each iteration. Finally, the inversion stability is improved, and the proposed inversion method, the block coordinate descent differential evolution simulated annealing (BCDESA) algorithm, is implemented. The performance of BCDESA is validated by using both synthetic data and field data from western China. The results show that the BCDESA algorithm has stronger global optimization capabilities than SA, and the inversion results have higher stability and accuracy. In addition, synthetic data analysis also shows that BCDESA can avoid the problems of the conventional SA method, which assumes the S-wave velocity structure in advance. The robustness and adaptability of the algorithm are improved, and more accurate shear-wave velocity and thickness information can be extracted from Rayleigh wave dispersion curves.

基于差分演化模拟退火算法的Rayleigh波频散曲线近地表速度反演
智慧城市对城市地下空间的利用,需要对地下结构有准确的认识。瑞雷波勘探作为一种有效的技术,能够准确地获取地下信息。特别是瑞利波频散曲线可以用来确定近地表横波速度结构。这是一个典型的多参数、高维非线性反演问题,因为每一层的速度和厚度必须同时反演。模拟退火(SA)等非线性方法通常用于求解这一逆问题。然而,SA通过温度而不是误差来控制迭代过程,并且搜索方向是随机的;因此,当温度设置不准确时,SA总是陷入局部最优。具体而言,对于瑞利波频散曲线的反演,由于反演参数较多、尺寸较大,反演精度会随着层数的增加而降低。为了解决上述问题,我们将多参数、高维的逆问题转化为多个低维的优化问题,并将块坐标下降(BCD)的原理融入到算法中,以提高算法的精度。然后,将原SA方法中的温度控制条件转化为误差控制条件。同时,引入差分进化(DE)方法,通过对每次迭代的迭代误差方向进行校正,保证迭代误差稳定减小。最后,提高了反演的稳定性,实现了所提出的块坐标下降差分进化模拟退火算法(BCDESA)。利用西部地区的综合数据和现场数据对BCDESA的性能进行了验证。结果表明,BCDESA算法比SA具有更强的全局优化能力,反演结果具有更高的稳定性和精度。此外,综合数据分析也表明,BCDESA可以避免传统SA方法提前假设s波速度结构的问题。提高了算法的鲁棒性和自适应性,可以从瑞利波色散曲线中提取更准确的横波速度和厚度信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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