Regularization analysis of three-dimensional magnetotelluric inversion

Inversion of MT data is an inherently nonunique and unstable problem due to the ill-posedness of the electromagnetic inverse problem. A variety of models may fit the data very well. To overcome this illposed nature of the inverse problem, we use Tikhonov’s regularization in which the ill-posed problem is replaced by a family of well-posed problems. We also analyze the behavior of the Tikhonov regularization parameter to find out its optimal value for a typical model of a hydrocarbon reservoir in a marine environment. We have compared two regularization techniques: rigorous and adaptive regularizations. The results of this numerical study demonstrate that adaptive regularization provides practically the same inverse image as the rigorous regularization, while reducing the computational time dramatically.