Deblending by sparse inversion: Case study on land data from Oman

Simultaneous shooting greatly improves the seismic acquisition productivity, but poses great challenge on the separation of interfering sources. In this paper, an inversion-based deblending method is presented, which distinguishes between signals and blending noise based on their coherency difference on receiver gathers and sparsity difference in frequency-wavenumber-wavenumber (FKK) domain. We demonstrate through two field datasets from Oman that the method is capable of separating the interfering vibroseis sources with high fidelity. In addition, to remove the residual blending noise caused by non-causal harmonics, we have improved the deblending algorithm and achieved better separation results. Presentation Date: Tuesday, September 17, 2019 Session Start Time: 1:50 PM Presentation Time: 3:30 PM Location: 221A Presentation Type: Oral