Development Of Joint Inversion Algorithm For MRS And TEM Data And MRS-TEM System For Groundwater Exploration

When the underground is conductive, the electrical conductivity will have a great effecton the Magnetic Resonance Sounding (MRS) signal and can not be ignored in the inversion.The traditional interpretation schemes of MRS used to be limited to the homogeneoushalf-space and take no account of the resistivity in the inversion, in turn resulting in theambiguous aquifer boundaries. Based on the MRS theory in the multi-layer earth model, wedeveloped a new scheme for joint inversion of MRS data and TransientElectromagnetic(TEM) data. By correcting MRS inversion with resistivity in real time, theaccuracy of inversion result was improved greatly. The Adaptive Genetic Algorithm(AGA)was applied. By adaptively adjusting the probability of crossover and mutation, AGA has notonly avoided the premature convergence of GA but also has obtained the global optimalsolution. On this basis, by simulating the effect of conductivity in forward and inversion ofMRS and for convenience in field experiment,we improved the performance and structureof MRS-TEM associated detection system. Finally three field experiments and applicationexamples are given. The main research contents and results are as follows:1. We study the magnetic field distribution produced by the surface gyrus line in layeredconductive medium and derive the magnetic resonance response expression of a layeredmedium model. By analyzing the responses of different layered resistivity models, aconclusion can be obtained that the resistivity information below100metres will stillinfluence the magnetic resonance signal. Among numerous geophysical techniques,MRS-TEM associated detection is the best solution. Comparing the magnetic resonanceresponses of different shallow resistivity models, it is concluded that the measureimproving TEM instrument performance must be taken to reduce detection blind area.2. In view of the standard genetic algorithm (GA),the adaptive genetic inversion algorithmwas put forward. According to the minimum resolution and the search space of modelparameters to determine the length of the chromosome; According to the individualdispersion and the average fitness to adaptively adjust the crossover and mutationprobability. By considering the value of the individual objective fuction and thedispersion of the group, the fitness function was designed. Using the AGA in the inversion of MRS and TEM data respectively, to vertify the effeciency of the algorithm.3. A method of joint inversion based on MRS–TEM data was put forward, which introduce the regularization inversion in detail and presents a parameter automatic adjustment method combining the stability of inversion results with computational efficiency. An objective function of MRS and TEM joint inversion is established with smooth model constraints and further narrows the searching space and reduces the uncertainty of inverse problem according to Archie’s law. At last, the MRS and TEM joint inversion scheme are designed in detail based on the AGA algorithm.The advantages of joint inversion is reflected in uniform half space models and layered models. Moreover, mixing noise of different SNR in the theoretical signal, the inversion results is still stable and reflect underground aquifer structure, even in the case of adding10%noise. Compared with the traditional MRS single inversion, the advantage is obvious.4. Considering the existing MRS-TEM associated system structure and aiming at the longdead-time of MRS and long turn-off time of TEM, a ’Q-Switch’ technique was used inMRS transmitting system to shorten the dead-time and improve the signal-to-noise ratio,a half-resonant&absorbing circuit was realized to shorten the TEM turn-off time anddecrease the TEM blind area.5. Joint inversion of MRS and TEM in this paper has been applied in the field to realizethe quantitative and qualitative imaging of groundwater, like BaiQi, Changchun, andLiaoning. The formation structure and the water unit structure obtained by the jointinversion can reach mutual authentication and are also supported by drilling data, bywhich the accuracy and the practical significance of the inversion method has been fullyverified.The main innovation lies as follow:By analyzing the impact of different resistivity distribution on MRS response, wefound that the resistivity information in the depths will still influence the MRSsignal. So I proposed that MRS and TEM associated detection method is the bestsolution among numerous geophysical techniques. The adaptive genetic inversion algorithm(AGA) I proposed can solve the slowconvergence speed and easy to fall into local optimal solution problem of thestandard genetic algorithm (GA). Use the AGA as the inversion algrithom ofJoint inversion of MRS and TEM for the first time, both the theoretical and fielddata vertified the effeciency of the algorithm.Joint inversion of MRS and TEM data was proposed. According to characteristicsof MRS and TEM response, the normalized objective function of joint inversionwas established, and the mutual constraints between the model parameters wererealized based on archie formula. By correcting the inversion process in real timeusing the resistivity distribution information, the accuracy of MRS interpretationresults can be improved greatly.The MRS and TEM detection system was improved by making the effect ofresistivity distribution on MRS response clear. A half-resonant&absorbingcircuit was realized to shorten the TEM turn-off time and decrease the TEM blindarea. A ’Q-Switch’ technique was used in MRS transmitting system to shortenthe dead-time and improve the signal-to-noise ratio.