MAGNETOTELLURIC APPRAISAL USING SIMULATED ANNEALING

Conductivity models derived from magnetotelluric measurements can be appraised by constructing extremal models which minimize and maximize localized conductivity averages. These extremal models provide lower and upper bounds for the conductivity average over the region of interest. Previous applications of this method have constructed extremal models via (iterated) linearized inversion; however, it is difficult to verify that the computed bounds represent global (rather than local) extrema. In this paper, a method of constructing extremal models using simulated annealing optimization is developed. Simulated annealing requires no approximations and is renowned for its ability to avoid unfavourable local minima. The optimization procedure is flexible and general, and can be applied to construct models which extremize a linear or non-linear objective function in any inverse problem for which the corresponding forward solution exists. Appraisal via simulated annealing is demonstrated using synthetic data and field measurements, and the results are compared with those based on linearization. The comparisons suggest that the bounds calculated via linearization represent excellent approximations to the global extrema.