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[1]LU Mingde.Deconvolution Optimization Algorithm of Seismic Signals Based on L1 Norm of Total Variation[J].Journal of Seismological Research,2023,46(01):107-115.[doi:10.20015/j.cnki.ISSN1000-0666.2023.0020 ]

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Deconvolution Optimization Algorithm of Seismic Signals Based on L¹ Norm of Total Variation

Journal of Seismological Research[ISSN 1000-0666/CN 53-1062/P] Volume: 46 Number of periods: 2023 01 Page number: 107-115 Column: 地震地下流体监测预报理论及技术应用专栏 Public date: 2023-01-01

Title:: Deconvolution Optimization Algorithm of Seismic Signals Based on L¹ Norm of Total Variation

Author(s):: LU Mingde; (Exploration and Development Research Institute of Liaohe Oilfield Company,Panjin 124010,Liaoning,China)

Keywords:: seismic signals; deconvolution; denoising; L¹ norm; the Total Variation theory; the alternating direction method of multipliers *

CLC:: P631

DOI:: 10.20015/j.cnki.ISSN1000-0666.2023.0020

Abstract:: Deconvolution is an effective method to improve the resolution of seismic signals.Due to the influence of noises,the stability of the sub-waves obtained by many deconvolution methods is poor,and the reflection coefficients are mixed with the sub-waves more seriously.In the light of the idea of norm optimization,a deconvolution optimization algorithm of seismic signals based on L¹ norm of total variation is proposed in this paper.Based on the L¹ norm of total variational theory,the seismic signal reconstruction model is constructed and transformed into a solution form conforming to iterative and alternating minimization.Then,the deconvolution optimization algorithm of seismic signals is designed by alternating direction multiplier method.The proposed algorithm does not need to consider the restrictions of deconvolution.It can effectively recover the seismic signals with noise,and improve the resolution and signal-to-noise ratio(SNR)of the seismic signals.Experiments on synthetic signals and field seismic data show that the algorithm improves the dominant frequency of sub-waves and widens the effective frequency band.It also performs well even if the signals are polluted by serious noises.

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Last Update: 2023-01-01