Efficient 3-D velocity model building using joint inline and crossline plane-wave wave-equation migration velocity analyses. Issue 1 (3rd December 2020)

• Record Type: Journal Article
• Authors: Liu, Xuejian; Huang, Lianjie; Feng, Zongcai; El-kaseeh, George; Will, Robert; Balch, Robert
• Is Part Of: Geophysical journal international. Volume 225:Issue 1(2021)
• Page Start: 37
• Page End: 53
• Publication Date: 2020-12-03
• Subjects: Inverse theory -- Joint inversion -- Tomography -- Waveform inversion -- Seismic noise; Geophysics -- Periodicals; 550
• DOI: 10.1093/gji/ggaa576
• Languages: English
• ISSNs: 0956-540X

Abstract

SUMMARY: Wave-equation migration velocity analysis (WEMVA) is an image-domain inversion method for velocity model building. Automatic plane-wave WEMVA (PWEMVA) calculates the moveouts of plane-wave common-image gathers (CIGs) by searching a best-fitting parabola with semblance analysis and backprojects residual CIG moveouts into wavefield wave paths with a reflection tomographic kernel. However, 3-D PWEMVA is very computationally expensive because 3-D reflection tomographic inversion requires at least five 3-D reverse-time migrations per iteration and stores two types of source wavefields at model boundaries. We develop a joint inline and crossline PWEMVA method for efficient 3-D velocity model building. We alternatively implement the inline and crossline PWEMVAs with a constraint for each other, in which we iteratively construct the 3-D velocity model update through 1-D spline interpolation of 2-D gradients. The inline and crossline joint inversion is practical since PWEMVA only inverts for low-wavenumber velocity perturbations along wave paths, and the method can take less than 1 per cent of the computational cost of full 3-D PWEMVA. To construct unaliased plane waves for our joint inline and crossline PWEMVA, we develop a 3-D data interpolation method in the frequency–wavenumber (FK) domain to recover regularly and randomly missing traces. The method minimizes the misfit on sufficiently localized data subsets with iterative optimal step lengths and a gradient preconditioner that iteratively selects dominant dips along different azimuths. In numerical experiments, we use a 3-D synthetic seismic data set and a land 3-D field seismic data set acquired at the Farnsworth CO2 -EOR (enhanced oil recovery) field to demonstrate the efficacy of our velocity model building and data interpolation methods.