A Kirchhoff migration imaging method based on grounded-source TEM virtual wave-fields and its applications

摘要

This research study was based on a Kirchhoff migration imaging method, and the aim of the study was to realize grounded-source transient electromagnetic virtual wave-field migration. Diffusion equations mainly characterize the induction characteristics of low-frequency electromagnetic waves which are not suitable for wavefields. Wave equations mainly characterize wave reflections, refractions, and other propagation features, which are suitable for wave-field imaging processes. A unique mathematical transformation relationship exists between the diffusion fields of transient electromagnetic fields and seismic wave-fields. After the transformations from diffusion fields to virtual wave-fields are achieved, seismic interpretation methods can be used for the transient electromagnetic data interpretations. First, in order to realize Kirchhoff migration imaging based on transient electromagnetic wave-fields, precondition regularization methods are used for the wave-field inverse transformations. Then, after obtaining the wave-field data, dynamic correction methods are adopted to convert the grounded-source transient electromagnetic virtual wave-fields to quasi-seismic zero offset data. At that point, a Kirchhoff integral can be applied to realize the grounded-source transient electromagnetic quasi-seismic migration imaging. A theoretical model was used to test the method which was proposed in this study. The results showed that the Kirchhoff migration imaging was able to determine the geometric formations of underground dielectric interfaces, which fully demonstrated the applicability of the proposed method. Finally, migration imaging processing was performed on the data obtained from a mining area, and the imaging results were found to be consistent with the known geological data. Therefore, the feasibility of using a wave-field transform method and Kirchhoff migration imaging technology for grounded-source transient electromagnetic data interpretations was successfully