Reflection-intensity waveform inversion

Liu, Yike (Institute of Geology and Geophysics, Chinese Academy of Sciences) | He, Bin (Institute of Geology and Geophysics, Chinese Academy of Sciences) | Zheng, Yingcai (University of Houston) | Xie, Xiao-Bi (University of California-Santa Cruz)

OnePetro 

Conventional full waveform inversion (FWI) needs long offset data to update the deep structure of a velocity and low-frequency information to avoid cycle skipping with diving or refraction waves. To reduce the data requirements, we propose an approach referred to as reflection intensity waveform inversion (RIWI), which fits the difference in seismic reflection intensity between modeled and field data, so that the starting model dependence of waveform inversion can be relaxed and long offset data is no longer required. The intensity inherently has low-frequency information when compared with the original data. It can be obtained by deconstructing the intensity into low-frequency and high-frequency information using Fourier transformation. Implementing multi-scale inversions starting from low-frequency reflection intensity data can largely avoid the cycle-skipping problem. We corroborate the proposed approach validity for data without low-frequency content and long-offset information with numerical examples.

Presentation Date: Monday, October 15, 2018

Start Time: 1:50:00 PM

Location: Poster Station 7

Presentation Type: Poster