Multisource least‐squares migration of marine streamer and land data with frequency‐division encoding

Abstract

Multisource migration of phase‐encoded supergathers has shown great promise in reducing the computational cost of conventional migration. The accompanying crosstalk noise, in addition to the migration footprint, can be reduced by least‐squares inversion. But the application of this approach to marine streamer data is hampered by the mismatch between the limited number of live traces/shot recorded in the field and the pervasive number of traces generated by the finite‐difference modelling method. This leads to a strong mismatch in the misfit function and results in strong artefacts (crosstalk) in the multisource least‐squares migration image. To eliminate this noise, we present a frequency‐division multiplexing (FDM) strategy with iterative least‐squares migration (ILSM) of supergathers. The key idea is, at each ILSM iteration, to assign a unique frequency band to each shot gather. In this case there is no overlap in the crosstalk spectrum of each migrated shot gather m(x, ωi), so the spectral crosstalk product m(x, ωi)m(x, ωj) =δi, j is zero, unless i=j. Our results in applying this method to 2D marine data for a SEG/EAGE salt model show better resolved images than standard migration computed at about 1/10th of the cost. Similar results are achieved after applying this method to synthetic data for a 3D SEG/EAGE salt model, except the acquisition geometry is similar to that of a marine OBS survey. Here, the speedup of this method over conventional migration is more than 10. We conclude that multisource migration for a marine geometry can be successfully achieved by a frequency‐division encoding strategy, as long as crosstalk‐prone sources are segregated in their spectral content. This is both the strength and the potential limitation of this method.

Full‐waveform inversion with multisource frequency selection of marine streamer data

“…; Etgen ; Vigh and Starr ; Ben‐Hadj‐Ali, Operto and Virieux ; Krebs et al . ; Tang and Biondi ; Boonyasiriwat and Schuster ; Godwin and Sava ; Huang and Schuster ; Dai, Huang and Schuster ). For example, 1000 shot gathers can be divided into 50 supergathers, each containing 20 shot gathers.…”

A cross-correlation objective function for least-squares migration and visco-acoustic imaging

“…Least-squares migration (LSM) has been shown to produce images with balanced amplitudes, better resolution and fewer artifacts than standard migration (Lailly, 1984;Schuster, 1993;Nemeth et al, 1999;Duquet et al, 2000;Tang, 2009;Wong et al, 2011;Huang and Schuster, 2012;Zhang et al, 2013). The improvements in the image quality from LSM are obtained by matching the amplitudes and phases of the predicted and the observed data under the Born approximation.…”

Least-squares reverse time migration of marine data with frequency-selection encoding

“…However, the random encoding functions used by Romero et al (2000), Krebs et al (2009), Schuster et al (2011) and Dai et al (2012), cannot be easily applied to a seismic survey with a marine streamer geometry (Routh et al, 2011;Huang and Schuster, 2012) because, although the calculated synthetic data are of fixed spread geometry, the observed data are recorded with a marine streamer geometry. Huang and Schuster (2012) proposed a frequency-selection encoding strategy for least-squares phase shift migration, which is applicable to marine data.…”