Joint inversion of MRS and TEM data based on adaptive genetic algorithm

The method of Magnetic Resonance Sounding (MRS) provides a new technology to determine subsurface water qualitatively and quantitatively, which has received much concern of geophysicists. The traditional inversion of MRS uses homogeneous half-space models and ignores effects of resistivity distribution on inversion results. Based on the MRS theory in the multi-layer earth model, we developed a new scheme for joint inversion of MRS data and Transient Electromagnetic (TEM) data. By correcting MRS inversion with resistivity in real time, the accuracy of inversion result was improved greatly. The Adaptive Genetic Algorithm (AGA) was applied. By adaptively adjusting the probability of crossover and mutation, AGA has not only avoided the premature convergence of GA but also has obtained the global optimal solution. Studies with synthetic data show that the MRS-TEM joint inversion scheme can obtain the aquifer structure accurately even 10% noise applied. Compared with the traditional MRS inversion scheme, the advantage of this new approach is obvious. By applying this method to filed data processing, and with the good inversion result, we have verified the the applicability of AGA and the practical significance of MRS-TEM joint inversion scheme.