Binary structure constrained gravity inversion based on seismic first arrival travel time data

Gravity exploration method is one of the important methods for deep mineral resource exploration, but gravity data inversion has limited resolution ability in the vertical direction. In order to improve the vertical resolution of gravity data inversion, we propose a binary structure constrained gravity inversion method based on seismic first arrival travel time data. This method effectively reconstructs a density model with high vertical resolution by transferring the structural information of a high-resolution velocity model reconstructed by seismic data inversion to gravity data inversion through the binary structure constrained technique. This strategy eliminates the need to integrate both gravity and seismic methods into a single inversion framework, avoiding both the difference in convergence speeds between the two methods, as well as getting rid of the complexity associated with calculating structural coupling terms. Theoretical simulations show that the fuzzy c-means cluster analysis technique can accurately extract the target region of the velocity model reconstructed by seismic data inversion. Under the constraint of seismic structural information, the resolution of reconstructed density model is much higher than that of separate gravity data inversion, which proves that high resolution seismic information can improve the vertical resolution of gravity data inversion. Compared with the traditional cross-gradient joint inversion, the binary structure constrained gravity inversion method can further improve the resolution of the density model, especially in the reconstruction of the anomaly interface, which verifies that the method has certain effectiveness.

Automated summary

The binary structure constrained gravity inversion method based on seismic data is proposed to improve the vertical resolution of gravity data inversion. By transferring the structural information from a high-resolution velocity model, the method successfully reconstructs a density model with higher resolution. The theoretical simulations and comparisons with traditional methods prove the effectiveness of the proposed method.