BUILDING ADJOINT OPERATORS FOR LEAST-SQUARES MIGRATION USING ACOUSTIC WAVE EQUATION

Seismic imaging can be solved as an inversion problem, which can be implemented as a least-squares migration (LSM). Compared to conventional migration algorithms, an LSM is able to produce imaging results with enhanced illumination and resolution. However, solving an inversion problem faces difficulties in convergence, stability, and computational efficiency. To address these issues, efforts have been spent on examining the key elements in an LSM, including the modeling operators, the migration operators, the inversion solvers, etc. Advanced modeling operators are developed to accurately simulate the seismic data. Innovative migration algorithms are implemented to precisely compute the subsurface image. Fast inversion solvers are used to improve computation efficiency. While all these techniques are robust to improve the LSMs, they are often studied independently. It is less considered whether these elements are properly combined when used in an LSM. In this paper, we construct LSMs with adjoint modeling and migration operators, and we propose algorithms to prepare input shot data for these LSMs.