Image gather reconstruction using StOMP

Discussion and Conclusions

Creating full 3-D angle gathers through cross-correlation gathers is currently computationally impractical given the volume size that needs to be read/written for every shot. Compressive sensing offers a potential solution to this problem by collecting a subset of the correlation gathers and then forming the entire volume after all shot contributions have been stacked. The StOMP algorithm appears to be an effective method to obtain a sparse basis function necessary for a successful compressive sensing effort. Phase encoding to encode multiple correlations into every data point appears to offer an improved result. Further work on full 3-D shift gathers is needed to prove the feasibility of the method.