Work

An Eikonal‐Based Angle‐Domain Least‐Squares Kirchhoff Depth Migration in General Anisotropic Media

Year: 2026

Type: article

Abstract: ABSTRACT Least‐squares migration (LSM) is an inversion‐based imaging method that seeks a reflectivity model whose predicted data best fit the recorded seismic data in a least‐squares sense. However, conventional LSM can be unreliable for anisotropic reflection data if reflection angles are neglected. First, ignoring anisotropic parameters often produces defocused images and biased kinematics. Second, conventional LSM is generally more sensitive to migration‐velocity errors than its extended‐angle counterpart. To address these limitations, we propose an angle‐domain least‐squares Kirchhoff depth migration (ADLSKDM) framework that explicitly accounts for general anisotropic effects via angle‐dependent linear inversion. Our workflow combines (i) a semi‐analytical eikonal solver that efficiently computes traveltimes in complex models under weak anisotropy, and (ii) a regularized least‐squares inversion that suppresses artefacts in angle‐domain common‐image gathers (ADCIGs). Numerical tests on anisotropic synthetic datasets demonstrate that ADLSKDM retrieves correct angle‐dependent kinematics with reduced ambiguity and fewer artefacts than conventional LSM.

Source: Geophysical Prospecting

DOI: 10.1111/1365-2478.70249

Authors: Paulo H. B. Alves, Wei Zhang, Mauricio D. Sacchi, Marco Cetale

Institutions: University of Alberta, Universidade Federal Fluminense

Language: English

Topic: Seismic Imaging and Inversion Techniques

Subfield: Geophysics

Field: Earth and Planetary Sciences

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $4,150

Funders: University of Alberta, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Division of Graduate Education