Gene

Computational science

Tectonics

Algorithm

Statistics

Geophysical imaging

Applied mathematics

Convergence (economics)

Wave equation

Computation

Economics

Biochemistry

Computer science

Mathematical optimization

Seismology

Geology

Least-squares function approximation

Prestack

Inversion (geology)

Mathematics

Estimator

Transcription factor

Mathematical analysis

Repressor

Chemistry

Geophysics

Economic growth

Inverse problem

Operator (biology)

Seismic migration

Seismic imaging can be solved as an inversion problem, which can be implemented as a least-squares migration (LSM). Compared with conventional migration algorithms, an LSM can 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. Although all these techniques are robust to improve the LSMs, they often are studied independently. It is not often considered whether these elements are properly combined when used in an LSM. We have constructed LSMs with adjoint modeling and migration operators, and we develop algorithms to prepare input shot data for these LSMs.

Building adjoint operators for least-squares migration using the acoustic wave equation