Seismic Acoustic Impedance Inversion Based on Arctangent Total Variation and Hybrid Domain Constraints.

Sparse acoustic impedance (AI) inversion methods are widely used in seismic processing and interpretation. Due to the insufficiency of the sparse representation and absence of time-frequency domain prior information in traditional sparse inversion methods, the inversion results have low accuracy in pinch-out points and thin layers. To overcome these barriers, a multitrace AI inversion method based on arctangent total variation and hybrid domain constraints is proposed. Different from the traditional L1 norm sparsity constraint, the arctangent total variation sparsity constraint can obtain sparser information, both in vertical and horizontal directions. This sparser information obtains more accurate boundaries and better continuity, which can reduce the error of inversion result in pinch-out points and thin layers. In addition, the hybrid domain constraint is utilized to introduce time-frequency domain prior information in the inversion. The time-frequency domain information can further improve the accuracy of the inversion. The alternating direction method of the multiplier algorithm, the Sylvester equation, and the proximity operator are utilized to solve the multiconstraint inversion problem. Numerous experimental results show that the proposed method can improve the accuracy of the inversion, especially in pinch-out points and thin layers.