Improved Algorithms Of Aeromagnetic Gradient Data And The Application In GeoProbe Platform

The processing method of aeromagnetic gradient date has become an important trend and direction at home and abroad. Faster and more accurate data processing methods and the corresponding software development has become an urgent problem to be solved in order to better exert the ability of geophysical prospecting data in solving various complex geological problems. We have made a research on the data preprocessing of airborne geophysical prospecting and the integration of the software on the basis of aerogeophysical data characteristics and the field data processing method is improved, mainly including the edge detection method, the local wave number method, and the Euler method. Model test and the actual data processing demonstrate the superiority of proposed methods.A new edge detection method based on tilt standard deviation method(TSTD) is proposed to deal with the problem of low accuracy of bit field boundary identification in aeromagnetic data processing. The method is based on potential field vertical to first-order derivative and the total horizontal derivative in the boundary position with different data characteristics(namely the vertical to a derivative in the boundary changes rate is the largest, the total horizontal derivative in the boundary changes rate minimum) is proposed and is realized by the standard deviation of the sliding window in the calculation of the two. TSTD method has good recognized edge continuity and small deviation with model edge comparing with the total horizontal derivative method, tilt angle method, theta map method and normalized standard deviation method, so it has strong detection capability.Local wavenumber method is an effective and practical method for estimating the depth and the nature(structural index) of the source. In this paper, we present two new potential-inversion methods based on the theoretical formulas of local wavenumber kx and kz. In the application of these two methods, we need to determine the maximum point of wavenumber ks and the corresponding horizontal coordinate first, and then combine this maxima and ks anomaly and different heights of ks using the corresponding calculation for computing the depth and structural index of the causative source.The fast automatic interpretation of the bit field data by the Euler inversion algorithm is another research focus of this paper. Conventional Euler deconvolution product method to construct the index of selection and dispersing solution, there are a lot of problems, based on simultaneous vertical derivative and analytic signal to a European lacy equation of the RDAS_Euler inversion method is proposed. The method can accurately estimate the range and depth of the field source, and does not need to consider the influence of the structural index N, which avoids the error caused by the improper construction index.Magnetic gradient tensor data can provide more information about the anomalies with higher resolution in contrast to the traditional magnetic anomaly data, having vast application prospect. We present a new edge identification method based on the analytic signal of magnetic gradient tensor, which can be derived by normalization of the ratio of first derivative and analytic signal in z directions. This method can reflect the edge of causative bodies exactly and reduce the noise interference effectively. I also demonstrate in this paper that the ratio of first derivative and analytic signal in x, y, z directions are homogeneous and satisfy Euler’s homogeneity equation, thus a linear equation can be acquired. This method allows the estimation of location parameters without any prior information about the nature(structural index) of the source, avoiding inversion errors that conventional Euler deconvolution method have caused by improper choice of structural index N.In order to improve the interpretation function of potential field data processing of Geo Probe platform, the proposed algorithm above is integrated with the Geo Probe platform, and the data processing function of the platform is enhanced, and the transformation of the method to the application module is realized. At the same time, the mapping function of Geo Probe platform is improved for better graphics display.