背景噪声互相关函数多尺度成像研究

The current research shows that the composition of the cross-correlation function (CCF) is relative complex, which contains the dispersion information from the multimodal surface waves, not only the fundamental -mode. The traditional imaging method of extracting fundamental-mode dispersion curve from the CCF has the risk of missing effective signals. Here, we proposed an imaging method only by using the CCF other than extracting information from the dispersion curve. Data-processing, forward modeling and inversion methods about the CCF are also studied in this research. In seismic exploration study, how to divide the stratigraphic grid and select the appropriate inversion frequency band is of great significance for high-precision imaging. This study proposed a new multi-scale inversion method, In this method, the layer thickness and inversion depth can be varied with different frequencies. Firstly, the coarser stratigraphic grids are divided, and the lower frequency-band information is selected to invert to obtain the underground largescale medium structure. This coarser grid division makes the inversion stable and requires less computation, but the resolution is limited, so the large-scale inversion result is re-divided into finer grids, and the higher frequency-band information is selected for inversion. This method can reduce the number of inversion parameters, improve the stability of inversion, reduce the computation cost, and ensure the model-resolution of the inversion result at the same time. Subsequently, the analysis of the field data verifies the feasibility of the proposed method. This noise cross-correlation function imaging method provides more options for the exploration of special areas where only few seismic stations can be deployed (such as the Moon, Mars and other extraterrestrial celestial bodies), and paves the way for the development of muti-scale imaging methods for complex media.