| 基于时延三维电阻率反演的岩溶地下河管道空间分布识别物理模拟研究 |
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| 引用本文： | 刘伟,周启友,潘晓东,何长响.基于时延三维电阻率反演的岩溶地下河管道空间分布识别物理模拟研究[J].中国岩溶,2022,41(2):298-307. |
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| 作者姓名： | 刘伟 周启友 潘晓东 何长响 |
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| 作者单位： | 1.南京大学地球科学与工程学院，江苏 南京 210046 |
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| 基金项目： | 国家重点研发计划项目“不同气候区喀斯特关键带水文—生态耦合过程对比研究”（2021YFE0107100）；中国地质调查局地质调查项目“乌江流域水文地质调查” (DD20190326) ；“南方重点地区1:5万页岩气地质调查”（DD20190562）；中国地质科学院岩溶地质研究所所控项目（2021003） |
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| 摘 要： | 岩溶地下河管道空间分布的识别对岩溶区的各类地球科学工作意义重大，文章阐述了采用时延三维电阻率反演技术，开展对地下河管道空间分布识别的研究，在室内灰岩介质下的物理模拟实验结果表明:对雨季管道充水和枯季管道干涸时采集的电阻率数据进行时延反演后，地下河管道的模拟三维空间分布被很好地突显出来，时延反演效果大大地优于对单次采集数据的反演效果，管道充填水时的反演效果次之，管道充填空气时的反演结果很难有效识别地下河管道的空间分布情况。物理模型试验成果可指导野外实践中对岩溶地下河管道的探测研究。
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| 关 键 词： | 地下河管道 空间分布 时延三维电阻率成像 物理模型 |
| 收稿时间： | 2021-01-09 |
Study on physical simulation of spatial distribution identification of karst underground pipeline based on time-lapse 3D resistivity inversion |
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| Institution: | 1.School of Earth Science and Engineering, Nanjing University, Nanjing, Jiangsu 210046, China2.Institute of Karst Geology, CAGS/Key Laboratory of Karst Dynamics, MNR & GZAR, Guilin, Guangxi 541004, China |
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| Abstract: | 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. |
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