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A method of seismic meme inversion and its application

Petroleum Exploration and Development 2020年第6期47卷 1235-1245页

作者： CHEN Yanhu BI Jianjun QIU Xiaobin CHEN Youbing YANG Hui CAO Jiajia DI Yongxiang ZHAO Haishan LI Zhixiang PEGETE Group Inc Beijing 100101China China University of Mining and Technology(Beijing) Beijing 100083China

Under the condition of thin interbeds with great lateral changes in terrestrial basins,a seismic meme inversion method is established based on the analysis of seismic sedimentology *** relationship between seismic waveform and high-frequency well logs is established through dynamic clustering of seismic waveform to improve the vertical and horizontal resolution of inversion results;meanwhile,by constructing the Bayesian inversion framework of different seismic facies,the real facies controlled inversion is *** forward model verification results show that the seismic meme inversion can realize precise prediction of 3 m thick thin interbeds,proving the rationality and high precision of the *** application in the Daqing placanticline shows that the seismic meme inversion could identify 2 m thin interbeds,and the coincidence rates of inversion results and drilling data were more than 80%.The seismic meme inversion method can improve the accuracy of reservoir prediction and provides a useful mean for thin interbeds prediction in terrestrial basins.

关键词： seismic inversion seismic waveform inversion facies controlled inversion reservoir prediction Daqing placanticline thin interbeds

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An improved Gaussian frequency domain sparse inversion method based on compressed sensing

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Applied Geophysics 2020年第3期17卷 443-452页

作者： Liu Yang Zhang Jun-Hua Wang Yan-Guang Liu Li-Bin Li Hong-Mei School of Geosciences China University of Petroleum(East China)Qingdao 266580China Geophysical Research Institute of Shengli Oilfi eld Branch Company SinopecDongying 257022China.

The traditional compressed sensing method for improving resolution is realized in the frequency *** method is aff ected by noise,which limits the signal-to-noise ratio and resolution,resulting in poor *** solve this problem,we improved the objective function that extends the frequency domain to the Gaussian frequency domain having denoising and smoothing ***,the reconstruction of the sparse refl ection coeffi cient is implemented by the mixed L1_L2 norm algorithm,which converts the L0 norm problem into an L1 norm ***,a fast threshold iterative algorithm is introduced to speed up convergence and the conjugate gradient algorithm is used to achieve debiasing for eliminating the threshold constraint and amplitude *** model test indicates that the proposed method is superior to the conventional OMP and BPDN *** not only has better denoising and smoothing eff ects but also improves the recognition accuracy of thin *** actual data application also shows that the new method can eff ectively expand the seismic frequency band and improve seismic data resolution,so the method is conducive to the identifi cation of thin interbeds for beach-bar sand reservoirs.

关键词： Compressed sensing Gaussian frequency domain L1-L2 norm thin interbeds beach-bar sand resolution signal-to-noise ratio

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