The Modeling And Inverse Of One Dimensional Time Domain Electromagnetic

The inverse problem of time-domain airborne electromagnetic data is still a hot spotin the field of airborne electromagnetic, with its own complexity and the large amountof data features, even one-dimensional inverse problems cannot be solved very well.Although the2.5-dimensional and three-dimensional time domain airborneelectromagnetic inversion have high accuracy, but its computational efficiency is toolow. At present one-dimensional time-domain airborne electromagnetic inverse is stillthe primary method for explain. In this paper we first discuss the time-domainairborne electromagnetic theory of one-dimensional forward and its modeling results.And then we study the1D inverse with damped least squares method and dampedeigenparameter method respectively. Including the followings:(1) Time domain airborne electromagnetic forward modeling. We carry out theforward calculation formula of a horizontally layered magnetic dipole source andcentral loop, which derived from the basic electromagnetic theory. Converting fromfrequency domain to time domain and Hankel transform are two keys in thecalculation, these two problems have directly impact on the final calculation results.In this paper, we use300-point filters for cosine transform and47-point filters forHankelJ1transform. Both of the results show that they are stable and highcomputational efficiency. Finally, we present the forward response results of typicalthree and four geoelectric model in the case of different flight altitudes and emissionmagnetic moment.(2) Damped least squares inverse. Here we discuss several key points in theinverse: the choice of damping factor, the establishment of the Jacobian matrix,iterative convergence criteria and inversion stopping criteria. The choice of thedamping factor is based on the degree of nonlinearity of the objective function to increase and decrease in this paper. While the traditional approach is according to thefunction values between two iterations, as there would be more inappropriate attemptto choice damping factor to affect the convergence rate. In the experimental part, weanalysis different geoelectric model inverse results by damped least squares method.(3) The damped eigenparameter inverse method. Here we also discuss the choiceof the damping factor, iterative convergence criteria and inversion stopping standard.Damped eigenparameter method combines the advantages of the Marquette methodand singular value truncated singular value decomposition. Dividing decomposedeigenvalues into important parameters and unimportant parameters, also truncatingsmall singular values. we constrain the inverse process by combining damping factorwith relative singular value and correcting iteratively damping factor. The methodintegrates all data features with fast and stable, compared with damped least squares.Finally, the experiments are still for three and four geoelectric model inverse,comparing with damped least squares method, results show that the method stableconvergence, high computational efficiency.