Least-squares Fourier finite-difference migration
最小二乘傅立叶有限差分偏移

Conventional migration algorithms utilize the inversion of a forward modeling operator by analytical means.Alternatively,least-squares migration method involves a numerical approach where the solution is retrieved by solving a linear discrete inverse problem.In this case,we intend to seek a model that fits the seismic data and exhibits some certain features.Least-squares migration reduces migration artifacts and generally produces very accurate seismic images.Kirchhoff operator is popularly used in the least-squares migration.However,many iterations are required and the methods have the drawbacks belong to the Kirchoff migration method.In this paper,we apply the least-squares technique to the wave equation migration methods based on wave extrapolation.An key to improve the efficiency of lease-squares migration is adopting efficient modeling and migrations operator.We perform least-squares migration using efficient Fourier finite-difference modeling and migration operators.Numerical examples show that the least-squares images can be efficiently retrieved in a few iterations of conjugate gradients method.In addition,we adopt the numerical software FFTW to perform Fourier transformation,which generally is more than six times quicker than conventional FFT programs,therefore the algorithm become more efficient.The algorithm can be easily implemented in parallel architecture.These features make the algorithm very attractive.