• 责任者：Wang Fei (College of Geo-Exploration Science and Technology ; Jilin University ; Changchun 130026 ; China) ; Liu Sixin
• 刊名：Chinese Journal of Geophysics
• 出版年：2013
• 卷期：56(11)
• 关键词：地质雷达 ; geological radar ; 层析技术 ; tomography
• 页码：p.3896-3907
• 图表：7 illus., 2 tables, 31 refs.
• 分类号：1600
• issnNo：ISSN0001-5733
• isbnNo：CN11-2074/P

     We perform a least square iteratively linearized inversion method for the crosshole radar traveltime tomography by using the observed first arrival data. In each iteration process, traveltimes are calculated by solving the traveltimes eikonal equation using the finite difference method and wavefront expansion is achieved by using the High Accuracy Fast Marching Method （HAFMM）, in other words, traveltimes are achieved by tracing wavefronts instead of rays. We test the suggested method on three assumed physical models with abnormal velocity areas. In model 1, three types of model parameter weighting matrix are introduced. In model 2, both FMM （Fast Marching Method） and HAFMM are considered to improve the accuracy of the inversion. In model 3, we also analyze three types of matrix inversion method, respectively. We also test our algorithm on a field data set from the Xiuyan giant jade, and we compared our scheme for the field data with the one obtained by a straight ray-tracing-based algorithm and the one obtained by a curve ray-tracing-based algorithm, respectively. The comparison results indicated that the reconstruction using the Laplace operator and HAFMM at the same time can get the best result, and there is almost no difference for the inversion result by using each one of the three types of matrix inversion method. And the wavefront traveltimes contour line of the synthetic data model implied the features and positions of the anomalous bodies. By comparison with the straight ray-tracing-based algorithm and curve ray-tracing-based algorithm, our scheme is able to generate a solution better than the one resulting from a curve ray-based scheme.