Improvement and application of preprocessing technique for multitrace seismic impedance inversion

Impedance inversion of post-stack seismic data is a key technology in reservoir prediction and characterization. Compared to the common used single-trace impedance inversion, multi-trace impedance simultaneous inversion has many advantages. For example, it can take lateral regularization constraint to improve the lateral stability and resolution. We propose to use the L2,0-norm of multi-trace impedance model as a regularization constraint in multi-trace impedance inversion in this paper. L2,0-norm is a joint-sparse measure, which can not only measure the conventional vertical sparsity with L0-norm in vertical direction, but also measure the lateral continuity with L2-norm in lateral direction. Then, we use a split Bregman iteration strategy to solve the L2,0-norm joint-sparse constrained objective function. Next, we use a 2D numerical model and a real seismic data section to test the efficacy of the proposed method. The results show that the inverted impedance from the L2,0-norm constraint inversion has higher lateral stability and resolution compared to the inverted impedance from the conventional sparse constraint impedance inversion.

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Improvement and application of preprocessing technique for multitrace seismic impedance inversion

Cited by 2 publications

References 22 publications

Model-data-driven AVO inversion method based on multiple objective functions

Model-data-driven AVO inversion method based on multiple objective functions

Seismic inversion with L2,0-norm joint-sparse constraint on multi-trace impedance model

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