Impedance inversion based on L1 norm regularization

• Add uniform and Gaussian noise into the synthetic record and invert the impedances with L1 norm regularization inversion method and damped least-squares inversion method.
• L1 norm regularization inversion method has better anti-noise ability and higher accuracy.
• Invert the reflection coefficients and impedances of the 2D field data with the extracted seismic wavelet.
• L1 norm regularization impedance inversion method has higher accuracy and better stability.

Impedance is an important parameter in geophysics which is greatly relevant to petroleum reservoir. Traditional iterative inversion methods, such as damped least-squares inversion method, often lead to unreliable inversion results when there is strong noise in the seismic records. In this paper, we propose a new impedance inversion method called L1 norm regularization inversion method which has high anti-noise ability. The accuracy of impedances derived from the proposed method is much higher than those derived from damped least-squares inversion method using synthetic seismic record and field data. We set up a forward simulation model and add different intensities of uniform and Gaussian noise into the synthetic seismic records respectively. We find that when there is strong noise in the synthetic record, L1 norm regularization inversion method can obtain the inverted impedance with higher accuracy compared with damped least-squares inversion method. At last, it is found that impedance derived from L1 norm regularization method has a higher accuracy than impedance derived from damped-squares inversion method when there is strong noise both in synthetic record and field data. We conclude that the proposed inversion method shows higher anti-noise ability and can provide impedances with higher accuracy.