Joint PP and PS plane-wave wave-equation migration-velocity analysis

Abstract
Conventional joint PP and PS velocity analysis is based on ray tomography. We develop a joint PP and PS wave-equation migration-velocity-analysis method using plane-wave common-image gathers (CIGs) to produce accurate P- and S-wave velocity models. The objective function of our new method consists of three terms: The first and second terms penalize the moveout residuals computed from PP and PS plane-wave CIGs, respectively, and the third term constrains the nonzero relative depth shifts between the PP and PS migration images. The moveout of plane-wave CIGs is automatically picked using a semblance analysis method, and the relative depth shifts between the PP and PS images are automatically computed using dynamic warping or manually picking the depths of certain primary reflectors. The moveout residuals and the relative depth shifts are transformed into weighted image perturbations, and they are then projected into the velocity models to update the P- and S-wave velocity models using the scalar-wave equations and their linearized forms. Numerical tests with synthetic and multicomponent field data demonstrate that our method can simultaneously invert for accurate P- and S-wave velocity models for elastic migration.

Citation
Feng, Z., Guo, B., & Huang, L. (2019). Joint PP and PS plane-wave wave-equation migration-velocity analysis. GEOPHYSICS, 84(4), R507–R525. doi:10.1190/geo2018-0521.1

Acknowledgements
This work was supported by U.S. Department of Energy through grant no. DE-AC52-06NA25396 to the Los Alamos National Laboratory (LANL). We thank VecVecta Oil & Gas Ltd. for providing us with the Kevin Dome seismic data. Z. Feng would like to thank the King Abdullah University of Science and Technology for funding his graduate studies. The computation was performed using supercomputers of LANL's Institutional Computing Program.

Publisher
Society of Exploration Geophysicists

Journal
GEOPHYSICS

DOI
10.1190/geo2018-0521.1

Additional Links
https://library.seg.org/doi/10.1190/geo2018-0521.1https://www.osti.gov/biblio/1542820

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