AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (4.6 MB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Original Paper | Open Access

Research on multi-wave joint elastic modulus inversion based on improved quantum particle swarm optimization

Peng-Qi Wanga, Xing-Ye Liub( ), Qing-Chun Lia( ), Yi-Fan Fenga, Tao Yanga, Xia-Wan Zhoua, Xu-Kun Hea
College of Geological Engineering and Geomatics, Chang'an University, Xi'an, 710054, Shaanxi, China
State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, College of Geophysics, Chengdu University of Technology, Chengdu, 610059, Sichuan, China

Edited by Meng-Jiao Zhou

Show Author Information

Abstract

Young's modulus and Poisson's ratio are crucial parameters for reservoir characterization and rock brittleness evaluation. Conventional methods often rely on indirect computation or approximations of the Zoeppritz equations to estimate Young's modulus, which can introduce cumulative errors and reduce the accuracy of inversion results. To address these issues, this paper introduces the analytical solution of the Zoeppritz equation into the inversion process. The equation is re-derived and expressed in terms of Young's modulus, Poisson's ratio, and density. Within the Bayesian framework, we construct an objective function for the joint inversion of PP and PS waves. Traditional gradient-based algorithms often suffer from low precision and the computational complexity. In this study, we address limitations of conventional approaches related to low precision and complicated code by using Circle chaotic mapping, Lévy flights, and Gaussian mutation to optimize the quantum particle swarm optimization (QPSO), named improved quantum particle swarm optimization (IQPSO). The IQPSO demonstrates superior global optimization capabilities. We test the proposed inversion method with both synthetic and field data. The test results demonstrate the proposed method's feasibility and effectiveness, indicating an improvement in inversion accuracy over traditional methods.

References

【1】
【1】
 
 
Petroleum Science
Pages 670-683

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
Wang P-Q, Liu X-Y, Li Q-C, et al. Research on multi-wave joint elastic modulus inversion based on improved quantum particle swarm optimization. Petroleum Science, 2025, 22(2): 670-683. https://doi.org/10.1016/j.petsci.2024.10.006

651

Views

9

Downloads

4

Crossref

2

Web of Science

5

Scopus

1

CSCD

Received: 19 April 2024
Revised: 19 July 2024
Accepted: 21 October 2024
Published: 22 October 2024
© 2024 The Authors.

This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).