Numerical modeling of elastic waves using the random-enhanced QPSO algorithm
Zhu Meng-quan, Wang Zhi-yang*, Liu Hong, Li You-ming, Yu Du-li
1. College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, PRC
2. Key Laboratory of Petroleum Resources Research, Institute of Geology and Geophysics, Chinese Academy of Sciences,
Beijing, PRC
3. University of Chinese Academy of Sciences, Beijing, PRC.
Abstract In this paper, we derive a random-enhanced quantum particle swarm optimization (QPSO) algorithm and develop a new finite difference (FD) scheme based on this algorithm. The random-enhanced QPSO algorithm has advantages of convergence speed and can converge within the 200th iteration. Under the same conditions, the convergence speed of the conventional QPSO algorithm is much lower than that of the random-enhanced QPSO algorithm. Numerical dispersion analysis reveals that the optimized FD scheme based on the random-enhanced QPSO algorithm has a broader spectral coverage, and the accuracy error is maintained within a valid range, signifying that the random-enhanced QPSO algorithm can better search for accurate global solutions. Finally, numerical modeling of elastic wave equations is performed using the optimized FD scheme based on the random-enhanced QPSO algorithm. The numerical modeling results indicate that the optimized FD scheme based on the random-enhanced QPSO algorithm can effectively suppress numerical dispersion
Fund: Qingdao National Laboratory for Marine Science and Technology “Stretch Correction Research and Parallel implementation
for Reverse-time migration of Multi-component Seismic Wave-field” (grant no. QNLM2016ORP0206), and the Fundamental
Research Funds for the Central Universities, BUCT “Research on Method of Elastic Vector Wave Field Imaging” (grant no.
ZY1924).
Corresponding Authors: Wang Zhi-yang E-mail: wangzy@mail.buct.edu.cn
E-mail: wangzy@mail.buct.edu.cn
About author: Mengquan Zhu received a B.S. degree at the Hebei University of Technology, China, in 2019. He is currently pursuing a master's degree at the College of Information Science and Technology, Beijing University of Chemical Technology,China
Cite this article:
. Numerical modeling of elastic waves using the random-enhanced QPSO algorithm[J]. APPLIED GEOPHYSICS, 2024, 21(1): 80-92.
2024, Vol. 21 
