Seismic migration problems and solutions

Abstract

Historically, seismic migration has been the practice (science, technology, and craft) of collapsing diffraction events on unmigrated records to points, thereby moving (“migrating”) reflection events to their proper locations, creating a true image of structures within the earth. Over the years, the scope of migration has broadened. What began as a structural imaging tool is evolving into a tool for velocity estimation and attribute analysis, making detailed use of the amplitude and phase information in the migrated image. With its expanded scope, migration has moved from the final step of the seismic acquisition and processing flow to a more central one, with links to both the processes preceding and following it. In this paper, we describe the mechanics of migration (the algorithms) as well as some of the problems related to it, such as algorithmic accuracy and efficiency, and velocity estimation. We also describe its relationship with other processes, such as seismic modeling. Our approach is tutorial; we avoid presenting the finest details of either the migration algorithms themselves or the problems to which migration is applied. Rather, we focus on presenting the problems themselves, in the hope that most geophysicists will be able to gain an appreciation of where this imaging method fits in the larger problem of searching for hydrocarbons.

Stolt's f-k migration for plane wave ultrasound imaging

“…In soft tissues, however, the speed of sound is not absolutely uniform [32] and one must therefore use an average or root-mean-square value. As with conventional focusing imaging [48], a mismatch in the speed of sound may significantly affect the quality of the images reconstructed by migration [49]. To illustrate the effect of a speed-of-sound mismatch in the context of plane wave imaging, image quality was determined in the Gammex phantom by repeating the migration processes with different speed values (the speed of sound within the Gammex phantom is claimed to be 1540 m/s).…”

Least-squares Reverse-time Migration

“…By contrast, conventional Kirchhoff migration usually calculates only one path from the sources and receivers to an image point. As a result, wavefield-continuation migration methods can produce superior images to conventional Kirchhoff migration for a complex model (Gray et al, 2001). …”

“…Consequently, wavefield-continuation migration methods have two advantages. First, compared to conventional Kirchhoff migration, wavefield-continuation migration methods do not use high-frequency (asymptotic) approximations and can therefore more accurately propagate wavefields in shallow depths (Gray et al, 2001). Second, wavefield-continuation migration methods can naturally handle multi-paths or multi-arrivals (Biondi, 2006).…”

“…The beams can overlap, so that the energy of one imaging point comes from sources and receivers with more than one path. This property allows Gaussian beam migration to address the multi-arrival or multi-path problem (Gray et al, 2001).…”

Computational optical coherence tomography [Invited]

“…Further insightful comparisons and connections between SAR and ISAM were discussed in Ref [74]. In addition to SAR, ISAM also shares a broad commonality with other systems applying computational imaging to multi-dimensional data collected using both spatial multiplex and time-of-flight measurements from a spectrallybroad temporal signal, such as synthetic aperture sonar [80], seismic migration imaging [81], and certain modalities in ultrasound [82] and photoacoustic imaging [83].…”