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Nonlinear prestack inversion using the reflectivity method and quantum particle swarm optimization

XINGYE LIU1 ,  XIAOHONG CHEN2 ,  LI CHEN3 ,  JINGYE LI
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2 State Key Laboratory of Petroleum Resources and Prospecting, National Engineering Laboratory for Offshore Oil Exploration, China University of Petroleum-Beijing, Beijing 102249, P.R. China.,
3 BGP INC, China National Petroleum Corporation Southwest Geophysical Research Institute, Chengdu 610000, P.R. China.,
JSE 2020, 29(4), 305–326;
Submitted: 21 May 2019 | Accepted: 9 March 2020 | Published: 1 August 2020
© 2020 by the Authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
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Abstract

Liu, X.Y., Chen, X.H., Chen, L. and Li, J-Y., 2020. Nonlinear prestack inversion using the reflectivity method and quantum particle swarm optimization. Journal of Seismic Exploration, 29: 305-326. The vectorized reflectivity method is an economical and reliable method for solving the elastic wave equation under a one-dimensional assumption. It can obtain the information of full wave field and accurately describe diverse propagation effects of the seismic wave. The inversion method based on the reflectivity method finds suitable inverted parameters by minimizing the error between the synthetic seismograms and observed seismic data. The non-linear inversion problem can be solved by a gradient-based method or a global optimization method. The former relies heavily on the staring model and is prone to fall into a local minima. The global optimization algorithms demand for an accurate and rapid calculation of the forward modeling. The vectorize reflectivity method satisfies these requirements. We introduce and improve the quantum particle swarm optimization algorithm (QPSO), which has significant advantages in global search, into seismic inversion based on the reflectivity method, developing a nove nonlinear prestack inversion method in angle gather domain. The vectorized reflectivity method is able to synthesize seismic records quickly and accurately. Using the QPSO relieves reliance on the initial model. The Cauchy distribution is introduced to combat the possible premature convergence. The benefits of the vectorized reflectivity method and QPSO are combined. We apply the technique to model data and field data, which demonstrates the feasibility and reliability of the new method.

Keywords
prestack inversion
reflectivity method
wave propagation effects
quantum particle swarm optimization
elastic wave equation
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Journal of Seismic Exploration, Print ISSN: 0963-0651, Published by AccScience Publishing
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