The effect of different arrays and noise source distribution on microtremor imaging and its application in solute salt mine cavity detection

With the rapid development of nodal seismometers, passive source seismic imaging methods have been widely used in the imaging of subsurface structures at different scales. For small-scale near surface imaging, due to the uneven spatial and temporal distributions of high-frequency noise sources, a method so-called microtremor imaging is generally used to extract high-frequency surface wave dispersion data, which is based on array averaging. However, different types of arrays can be affected by uneven distribution of noise sources. In this study, for imaging salt mine cavities, we systematically analyze the response functions of different arrays and their ability to resolve noise sources from different azimuths. It is found that the triangular array can obtain more reliable surface wave dispersion curve, but it is more inefficient to collect the corresponding data. In comparison, for other types of arrays, although it is relatively more efficient to deploy them, the extracted surface wave phase velocities may deviate greatly from true ones. When the linear array approximately aligns with the azimuth of the steady noise source, the surface wave dispersion curve can be reliably extracted, which is consistent with or even better than that from the triangular array. Based on the above analysis, we deploy two profiles that use the triangular array and the noise source aligned linear array for microtremor imaging of cavities in the Xiangheng salt mine, respectively. The extended spatial auto-correlation method (ESPAC) which has the better adaptability is used to calculate the surface wave dispersion data. Finally, the dispersion data is inverted for shear wave velocity model with random initial models generated by the Monte Carlo method. We have obtained detailed shear wave velocity models shallower than 600 m along two profiles and determined the location of the salt cavity and its morphology.