地球与行星物理论评（中英文）2026，Vol.57Issue(3)：242-270,29.DOI:10.19975/j.dqyxx.2025-019
勘探地震学最小二乘偏移成像进展综述
Review on the progress of least-squares migration in exploration seismology
摘要
Abstract
Seismic imaging plays an important role in the discovery of deep discontinuities,mineral explora-tion,oil and gas prospecting and development,as well as geological surveys.Over the past half-century,with the rapid advancement of high-performance computing and advanced data acquisition,seismic imaging methods have undergone an evolution from traditional ray-based migration to wave-equation imaging,and further to least-squares migration(LSM)and full-waveform inversion(FWI)imaging.By solving a linear or nonlinear inversion problem,inversion-based migration estimates a generalized inverse of the subsurface reflectivity model,which overcomes the limitations of conventional adjoint-operator-based migration methods in irregular acquisition,limited-band-width data,and unbalanced illumination.It can significantly enhance imaging resolution and amplitude fidelity.We systematically review the progress and cutting-edge developments of inversion-based migration in exploration seis-mology,especially focusing on the theory and methodology of data-domain,image-domain and intelligent LSMs.Additionally,we describe various regularization and preconditioning strategies for LSM in terms of their mathem-atical principles and practical effectiveness.Finally,we discuss the latest development in nonlinear FWI imaging,offering theoretical and methodological references for high-precision seismic imaging studies.关键词
地震成像/最小二乘偏移/全波形反演成像/计算地震学Key words
seismic imaging/least-squares migration/full-waveform inversion imaging/computational seis-mology分类
天文与地球科学引用本文复制引用
杨继东,黄建平,祝贺君,李振春,卢绍平,毛伟建,周辉,秦宁,田坤..勘探地震学最小二乘偏移成像进展综述[J].地球与行星物理论评（中英文）,2026,57(3):242-270,29.基金项目
国家自然科学基金优秀青年科学基金项目(海外)(202211333) （海外）
国家自然科学基金面上资助项目(42474136) （42474136）
山东省自然科学基金面上资助项目(ZR2023MD087) （ZR2023MD087）
山东省国家级领军人才配套(ZX20230018) （ZX20230018）
东营市自然科学基金(2023ZR07)Supported by the National Natural Science Foundation of China Excellent Young Scientists Fund(Overseas)(Grant No.202211333),National Natural Science Foundation of China(Grant No.42474136),Natural Science Foundation of Shandong Province-General Program(Grant No.ZR2023MD087),Shandong Province Leading Talent Support(Grant No.ZX20230018),and Natural Science Foundation of Dongying(Grant No.2023ZR07) （2023ZR07）
