Sparse constrained encoding multi-source full waveform inversion method based on K-SVD dictionary learning

作     者：Guo Yun-dong Huang Jian-Ping Cui Chao LI Zhen-Chun LI Qing-Yang Wei Wei 国运东;黄建平;崔超;李振春;李庆洋;魏巍

作者机构：School of GeosciencesChina University of Petroleum(East China)Qingdao 266580China Laboratory for Marine Mineral ResourcesQingdao National Laboratory for Marine Science and TechnologyQingdao 266071China Geophysical Exploration Research Institute of Zhongyuan Oilfi eld CompanyPuyang 457001China SINOPEC Petroleum Exploration and Production Research InstituteBeijing 100083China 

出 版 物：《Applied Geophysics》 (应用地球物理（英文版）)

年 卷 期：2020年第17卷第1期

页      面：111-123,169页

核心收录：

学科分类：081801[工学-矿产普查与勘探] 081802[工学-地球探测与信息技术] 0707[理学-海洋科学] 08[工学] 0708[理学-地球物理学] 0818[工学-地质资源与地质工程] 0825[工学-航空宇航科学与技术] 0704[理学-天文学] 

基　　金：jointly supported by the National Science and Technology Major Project(Nos.2016ZX05002-005-07HZ,2016ZX05014-001-008HZ,and 2016ZX05026-002-002HZ) National Natural Science Foundation of China(Nos.41720104006 and 41274124) Chinese Academy of Sciences Strategic Pilot Technology Special Project(A)(No.XDA14010303) Shandong Province Innovation Project(No.2017CXGC1602) Independent Innovation(No.17CX05011) 

主　　题：K-SVD dictionary sparsity constraint polarity encoding multi-source full waveform inversion 

摘      要：Full waveform inversion(FWI)is an extremely important velocity-model-building ***,it involves a large amount of calculation,which hindsers its practical *** multi-source technology can reduce the number of forward modeling shots during the inversion process,thereby improving the ***,it introduces crossnoise *** this paper,we propose a sparse constrained encoding multi-source FWI method based on K-SVD dictionary *** phase encoding technology is introduced to reduce crosstalk noise,whereas the K-SVD dictionary learning method is used to obtain the basis of the transformation according to the characteristics of the inversion *** multiscale inversion method is adopted to further enhance the stability of ***,the synthetic subsag model and the Marmousi model are set to test the effectiveness of the newly proposed *** of the results suggest the following:(1)The new method can effectively reduce the computational complexity of FWI while ensuring inversion accuracy and stability;(2)The proposed method can be combined with the time-domain multi-scale FWI strategy flexibly to further avoid the local minimum and to improve the stability of inversion,which is of significant importance for the inversion of the complex model.