Study on physical simulation of spatial distribution identification of karst underground pipeline based on time-lapse 3D resistivity inversion

The spatial distribution of karst underground river pipelines is complex and changeable; therefore, it is of great significance for us to carry out the earth science work in karst areas to develop an effective detection technology for the identification of pipelines. Based on the characteristics that karst underground river pipelines change greatly with seasons and time, the spatial distribution identification of underground river pipelines is studied by the inversion technology of time-lapse 3D resistivity. The results of pilot physical model experiments in limestone medium show that, the spatial distribution of simulated three-dimensional underground river pipeline is well highlighted according to the time-delay inversion imaging of resistivity data respectively collected from water-filled pipelines in rainy season and air-filled pipelines in dry season, The area with large resistivity change is in good agreement with the actual spatial position of pipeline in transverse and longitudinal directions. The closer the resistivity is to the center of the pipeline, the more significant the resistivity change is. In terms of the electrical sounding curve, the resistivity presents a low-high-low feature, and the resistivity contrast between pipeline space and other depth intervals is significant. In terms of the electrical sounding gradient curve, both the gradient value of pipeline space near the overlying clay layer and the value underlying limestone layer are large. The gradient value is positive near the upper contact surface and negative near the lower contact surface. The inversion effect with water-filled pipeline is inferior to that of time-lapse inversion. When the simulated pipeline is filled with water, the pipeline space presents relatively low resistivity. The resistivity value at the bottom of the pipeline is greater than that of the upper part, and the actual spatial position of the pipeline can be effectively reflected. The resistivity presents a high-low-high curve on the electrical sounding curve. However, on the electrical sounding gradient curve, the gradient value of the pipeline space near the overlying clay layer is negative, and it is positive near the underlying limestone layer. It is difficult to effectively identify the karst pipeline through the inversion images only generated by air-filled data. The resistivity rises monotonously and the resistivity value in the pipeline space changes more quickly than that in other depth intervals on the electrical sounding curve, while on the electrical sounding gradient curve, the resistivity gradient value in the pipeline space is slightly larger than that in other depth intervals, but the anomaly in the pipeline space is very weak compared with the time-lapse inversion results and water filling inversion results. It is suggested that when the spatial distribution of underground river pipelines in the field is studied, the 3D resistivity data should be collected in wet season and dry season, respectively, and the time-lapse 3D resistivity inversion image, electric sounding curve and electric sounding gradient curve can be comprehensively analyzed for the research. The subordinate choice is to carry out 3D detection of karst pipeline in wet season and analyze the data comprehensively, so as to obtain a practical detection technology that can effectively locate the underground river pipeline whether it is filled with water or free of water, which can be popularized and applied in practice.