An Application of Elastic-Net Regularized Linear Inverse Problem in Seismic Data Inversion

In exploration geophysics, seismic impedance is a physical characteristic parameter of underground formations. It can mark rock characteristics and help stratigraphic analysis. Hence, data inversion for key technology in oil gas reservoir prediction. To invert from data, one perform reflectivity series first. Then, under simple exponential integration transformation, the inverted give final impedance. The quality directly affects Sparse-spike most common method to obtain with high resolution. adopts sparse regularization impose sparsity on series. However, resolution sparse-spike-like obtained at cost sacrificing small reflectivity. This inherent problem regularization. fact, actual well log not strictly sparse. contains only major large reflectivity, but also between That say, sparse, dense. combat this issue, we adopt elastic-net replace inversion. elastic net hybrid that combines dense proposed was performed synthetic trace, which created an log. real profile used test practice application. results showed it provides effective new alternative