oa “Unsmooth” 1D inversion of frequency domain marine controlled source EM data

The goal of geophysical inversion of electromagnetic (EM) data is to recover a model of the geoelectrical properties of the sub-surface. The standard practice for 1D inversion of marine controlled source EM (CSEM) data is to generate smooth conductivity models using least squares (L2-norm) methods. However, sedimentary geology is stratified and piece-wise continuous. As such, smooth resistivity models cannot represent this character. In response to this inconsistency, a means was sought to generate more geologically plausible, piece-wise continuous models.

The common approach in the literature when generating piece-wise continuous inversion models is to regularize L2-norm methods in such a manner as to induce blocky behaviour. Although effective, these techniques are selfconflictive; forcing non-smooth behaviour from an implicitly smooth algorithm. In contrast, L1-norm inversion inherently produces piece-wise continuous models. To investigate the possible utility of this approach, a L1-norm inversion algorithm has been developed and tested on synthetic and real datasets. The L1-norm results were compared with those generated using an industry standard L2-norm algorithm.

The synthetic inversions focused on previously published examples. The real data inversions focused on electric and magnetic field measurements recorded over the main reservoir sand of the Pluto gas field in block WA350-P, North West Shelf, WA.

The L1-norm inversions recovered, to within the resolution limits of the CSEM method, the depth, thickness and resistivity of the synthetic geological models and the Pluto-1 resistivity well log, whilst fitting the input data to within noise. When compared against the L2-norm profiles, the L1-norm inversion more closely represented the stratified character of the sedimentary sequence. It was therefore concluded that L1-norm inversion is an attractive alternative to smooth L2-norm methods when blocky inversion models are desired.