Flexible quasi-2D inversion of time-domain AEM data, using a wavelet-based complexity measure

Regularization methods improve the stability of ill-posed inverse problems by introducing some a priori characteristics for solution such as smoothness or sharpness. In this contribution, we propose multidimensional, scale-dependent wavelet-based L1-regularization term to cure ill-posedness airborne (time-domain) electromagnetic induction problem. The regularization is flexible, it can recover blocky, smooth and tunable in-between inversion models, based on suitable wavelet basis function. For each orientation, different function be used, an additional relative parameter. We calibration method determine (an educated initial guess for) parameter, which reduces need optimize and, consequently, overall computation time under control. apply our novel scheme time-domain data set in Belgian saltwater intrusion context, but could equally any other 2D 3D geophysical