Least-squares reverse time migration for the Cascadia ocean-bottom dataset

Least-squares reverse time migration for the Cascadia ocean-bottom dataset

Mandy Wong, Shuki Ronen, and Biondo Biondi

Abstract:

We present a method based on least-squares reverse time migration (LSRTM) for imaging ocean-bottom data. We show that by using LSRTM, we not only enhance the resolution of the image but also suppress the migration artifacts. Furthermore, LSRTM also raise the relative amplitude of true reflectors in the subsurface. This method can also be extended to imaging with higher-order multiples. In certain geometries, LSRTM with multiples can further improve the image with a larger aperture. We demonstrate the concept and methodology in 2D and apply our proposed scheme to an ocean-bottom field survey located in the northern Cascadia continental margin.