Experimental study on various factors contributing to poor microtremor data processing results using ESAC method

In practical applications, microtremor data often encounter contamination from various sources of noise, leading to suboptimal processing outcomes. This study aimed to provide a comprehensive analysis of the impact of noise on the microtremor method. The focus was on presenting explicit and quantitative evidence to demonstrate the extent to which these noises influence the accuracy and reliability of the method. Initially, a ten-station triangular array was employed to gather a sequence of high-precision microtremor data. Next, various influencing factors, such as high-amplitude random noise, were generated and incorporated into the meticulously collected real data in order to simulate the actual perturbation process. Based on both the raw and the artificially contaminated data, a series of dispersion curves of the fundamental-mode Rayleigh waves were obtained by applying the extended spatial autocorrelation method (ESAC). Based on the obtained results, several valuable conclusions have been derived that can effectively inform the procedures for acquiring and processing microtremor data. If the amplitude and duration of sudden onset vibrations are considerable, more data should be collected to reduce the Negative impact. If non-random noise exhibits similar frequency characteristics as microtremor data, and the duration and energy of the noise are relatively small, it can be ignored; otherwise, more data should be collected. The dispersion curve, determined by the principle of the ESAC method, remains unaffected by any changes in the amplitude of one or more traces. The likelihood of frequency dispersion curve distortion increases as the impact of entire data anomalies on the coherence curve becomes greater. In general, when the collection positions of abnormal data are more widely spaced, the impact on the frequency dispersion curve tends to decrease. It is important to note that, in a nested-triangular array configuration, the central geophone plays a crucial role in ensuring accurate and dependable outcomes.