Least-squares migration/inversion of blended data

Least-squares migration/inversion of blended data

Yaxun Tang and Biondo Biondi

Abstract:

We present a method based on least-squares migration/inversion to directly image data collected from recently developed wide-azimuth acquisition geometries, such as simultaneous shooting and continuous shooting, where two or more shot records are often blended together. We show that by using least-squares migration/inversion, we not only enhance the resolution of the image, but more importantly, we also suppress the crosstalk or acquisition footprint, without any pre-separation of the blended data. We demonstrate the concept and methodology in 2-D and apply the data-space inversion scheme to the Marmousi model, where an optimally reconstructed image, free from crosstalk artifacts, is obtained.