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• W2893529635 abstract "Summary The elastic parameter inversion technique for prestack seismic data, which combines the intelligent optimization algorithms with Amplitude Variation with Offset (AVO) technology, is an effective method for oil and gas exploration. However, when certain biological‐evolution–based optimization algorithms, eg, genetic algorithms, are used to solve this problem, the computation exhibits fast convergence and a strong tendency to be trapped to a local optimum, thereby leading to unsatisfactory inversion results. To address this issue, this paper proposes a swarm‐intelligence‐based method‐Particle Swarm Optimization (PSO) algorithm to handle the elastic parameter inversion problem. Based on the Aki‐Richards approximation to the Zoeppritz equations, the improved PSO algorithm adopts a special initialization strategy, which can enhance the smoothness of the initialization parametric curves. Extensive experimental research confirms the superiority of the proposed algorithm. Specifically, the improved PSO algorithm is able to not only markedly enhance inversion precision but also render remarkably high correlation coefficients associated with the elastic parameters." @default.
• W2893529635 created "2018-10-05" @default.
• W2893529635 creator A5000789681 @default.
• W2893529635 creator A5013105439 @default.
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• W2893529635 date "2018-09-21" @default.
• W2893529635 modified "2023-10-08" @default.
• W2893529635 title "An improved particle swarm optimization algorithm for AVO elastic parameter inversion problem" @default.
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• W2893529635 doi "https://doi.org/10.1002/cpe.4987" @default.
• W2893529635 hasPublicationYear "2018" @default.
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