Seismic reflection data interpolation with differential offset and shot continuation

Conclusions

Differential offset continuation provides a valuable tool for interpolation and regularization of seismic data. Starting from analytical frequency-domain solutions of the offset continuation differential equation, I have designed accurate finite-difference filters for implementing offset continuation as a local convolutional operator. A similar technique works for shot continuation across different shot gathers. Missing data are efficiently interpolated by an iterative least-squares optimization. The differential filters have an optimally small size, which assures high efficiency.

Differential offset continuation serves as a bridge between integral and convolutional approaches to data interpolation. It shares the theoretical grounds with the integral approach but is applied in a manner similar to that of prediction-error filters in the convolutional approach.

Tests with synthetic and real data demonstrate that the proposed interpolation method can succeed in complex structural situations where more simplistic methods fail.