Diffraction separation and imaging based on double sparse transforms

作     者：Xue Chen Jing-Jie Cao He-Long Yang Shao-Jian Shi Yong-Shuai Guo Xue Chen;Jing-Jie Cao;He-Long Yang;Shao-Jian Shi;Yong-Shuai Guo

作者机构：Hebei Key Laboratory of Strategic Critical Mineral ResourcesHebei GEO UniversityShijiazhuangHebei 050031China Hebei Nautral Resources ArchivesShijiazhuangHebei 050037China The Third Hydrogeological Engineering Geological BrigadeHengshuiHebei 053000China 

出 版 物：《Petroleum Science》 (石油科学（英文版）)

年 卷 期：2022年第19卷第2期

页      面：534-542页

核心收录：

学科分类：070207[理学-光学] 07[理学] 08[工学] 080203[工学-机械设计及理论] 0802[工学-机械工程] 0803[工学-光学工程] 0702[理学-物理学] 

基　　金：supported by National Natural Science Foundation of China(41974166) Natural Science Foundation of Hebei Province(D2019403082,D2021403010) Hebei Province“three-threethree talent project”(A202005009) Funding for the Science and Technology Innovation Team Project of Hebei GEO University(KJCXTD202106) 

主　　题：Diffraction separation Common-offset domain Diffraction imaging High-resolution linear Radon transform Curvelet transform Sparse inversion 

摘      要：Reflection imaging results generally reveal large-scale continuous geological information,and it is difficult to identify small-scale geological bodies such as breakpoints,pinch points,small fault blocks,caves,and fractures,*** imaging is an important method to identify small-scale geological bodies and it has higher resolution than reflection *** the common-offset domain,reflections are mostly expressed as smooth linear events,whereas diffractions are characterized by hyperbolic *** paper proposes a diffraction extraction method based on double sparse *** linear events can be sparsely expressed by the high-resolution linear Radon transform,and the curved events can be sparsely expressed by the Curvelet transform.A sparse inversion model is built and the alternating direction method is used to solve the inversion *** data and field data experimental results proved that the diffractions extraction method based on double sparse transforms can effectively improve the imaging quality of faults and other small-scale geological bodies.