Seismic impedance inversion via L0 gradient minimisation

Abstract

Impedance inversion performed on post-stack seismic data is one approach to reservoir prediction. Conventional post-stack seismic data inversion has two main stages. Stage one involves deconvolution to estimate reflectivities and stage two is estimation of the impedance section from these reflectivities. These two stages are ill-posed inverse problems due to the nature of seismic inversion. An alternative method has been proposed that combines the two stages to estimate seismic impedance directly. Because it is less sensitive to noise in the seismic data, the proposed method decreases the inherent ill-posedness of impedance inversion. To regularise this merged inverse problem, L0 gradient minimisation of impedance has been used. L0 gradient minimisation regularisation provides a blocky impedance solution that makes formation interfaces and geological edges more precise and keeps the inversion procedure robust even if random noise exists in the seismic data. A split-Bregman-like algorithm has been used to solve the L0 gradient minimisation problem. The results of numerical examples show that the proposed inversion method can generate more accurate impedance models compared with conventional methods. Finally, the proposed method is applied to real seismic data from east China to test its applicability in practice. The inversion results confirm that the proposed method is effective at inverting real seismic data.