Seismic data interpolation using nonlinear shaping regularization

Published as Journal of Seismic Exploration, 24, no. 5, 327-342, (2015)

Seismic data interpolation using nonlinear shaping regularization

Yangkang Chen, Lele Zhang and Le-wei Mo
Bureau of Economic Geology
John A. and Katherine G. Jackson School of Geosciences
The University of Texas at Austin
University Station, Box X
Austin, TX 78713-8924

Institute of Geology and Geophysics,
Chinese Academy of Sciences,
Beijing, China, 102200

Research and Development Technology Group, Fairfield Nodal,
1111 Gillingham Lane,
Sugar Land, TX 77478

Abstract:

Seismic data interpolation plays an indispensable role in common seismic data processing workflows. Iterative shrinkage thresholding (IST) and projection onto convex sets (POCS) can both be considered as a specific form of nonlinear shaping regularization. Compared with linear form of shaping regularization, the nonlinear version can be more adaptive because the shaping operator is not limited to be linear. With a linear combination operator, we introduce a faster version of nonlinear shaping regularization. The new shaping operator utilizes the information of previous model to better constrain the current model. Both synthetic and field data examples demonstrate that the nonlinear shaping regularization can be effectively used to interpolate irregular seismic data and the proposed faster version of shaping regularization can indeed get obvious faster convergence.

Seismic data interpolation using nonlinear shaping regularization