Least-squares Migration/inversion of Blended Data

We present a method based on wave-equation least-squares migration/inversion to directly image data collected from recently developed wide-azimuth acquisition geometry, 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 preseparation 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.