Multisource Least-squares Reverse Time Migration

Abstract

Least-squares migration has been shown to be able to produce high quality migration images, but its computational cost is considered to be too high for practical imaging. In this dissertation, a multisource least-squares reverse time migration algorithm (LSRTM) is proposed to increase by up to 10 times the computational efficiency by utilizing the blended sources processing technique.

There are three main chapters in this dissertation.

In Chapter 2, the multisource LSRTM algorithm is implemented with random time-shift and random source polarity encoding functions. Numerical tests on the 2D HESS VTI data show that the multisource LSRTM algorithm suppresses migration artifacts, balances the amplitudes, improves image resolution, and reduces crosstalk noise associated with the blended shot gathers. For this example, multisource LSRTM is about three times faster than the conventional RTM method. For the 3D example of the SEG/EAGE salt model, with comparable computational cost, multisource LSRTM produces images with more accurate amplitudes, better spatial resolution, and fewer migration artifacts compared to conventional RTM. The empirical results suggest that the multisource LSRTM can produce more accurate reflectivity images than conventional RTM does with similar or less computational cost. The caveat is that LSRTM image is sensitive to large errors in the migration velocity model.

In Chapter 3, the multisource LSRTM algorithm is implemented with frequency selection encoding strategy and applied to marine streamer data, for which traditional random encoding functions are not applicable. The frequency-selection encoding functions are delta functions in the frequency domain, so that all the encoded shots have unique non-overlapping frequency content. Therefore, the receivers can distinguish the wavefield from each shot according to the frequencies. With the frequency-selection encoding method, the computational efficiency of LSRTM is increased so that its cost is comparable to conventional RTM in the examples of the Marmousi2 model and a field data set from the Gulf of Mexico. With more iterations, the LSRTM image quality is further improved. The numerical results suggest that LSRTM with frequency-selection is an efficient method to produce better reflectivity images than conventional RTM.

In Chapter 4, I present an interferometric method for extracting the diffraction signals that emanate from diffractors, also denoted as seismic guide stars. The signal-to-noise ratio of these interferometric diffractions is enhanced by √N, where N is the number of source points coincident with the receiver points. Thus, diffractions from subsalt guide stars can then be rendered visible and so can be used for velocity analysis, migration, and focusing of subsalt reflections. Both synthetic and field data records are used to demonstrate the benefits and limitations of this method.