Optimizing 4D hydrogeological process monitoring using cross-hole electrical resistivity tomography (CHERT) via Bayesian experimental design
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摘要:
地球物理方法可以有效监测四维水文地质过程中水流的动态和物质的传输，其成像精度往往与监测布置方案密切相关。以常用的高密度电阻率法（electrical resistivity tomography，简称ERT）为例，为了获得良好的成像精度往往需要大量的电极排列，导致监测时间较长，因而不能实时响应四维水文地质动态过程。已有ERT监测方案优化研究多侧重地表ERT，很少针对跨孔ERT。由于跨孔ERT在研究区域高精度刻画方面更具优势，提出了采用贝叶斯实验设计优化跨孔ERT监测方案。通过室内静态/动态实验以及野外场地数据，对比优化电极排列与传统电极排列的监测时间与监测精度，验证了贝叶斯实验设计优化方案的有效性。室内实验结果表明：优化后监测方案能减少约75%的监测时间，而且优化方案反演结果能更精准地动态刻画电阻异常区域，显著改善传统方案监测四维水文地质过程的滞后性误差。野外场地实验验证表明：在保证监测精度的前提下优化方案可减少约95%的监测时间。基于贝叶斯实验设计优化跨孔ERT电极排列监测方案为四维水文地质过程的高效监测提供了技术支撑。
Abstract:Objective Geophysical methods can effectively monitor the dynamics of water flow and material transport in 4D hydrogeological processes, and its imaging accuracy is often closely related to the monitoring scheme. Taking the commonly used electrical resistivity tomography (ERT) as an example, obtaining good imaging accuracy often requires a large number of electrode arrays, leading to a long data acquisition time and inability to respond in a timely manner to 4D hydrogeological dynamics. Previous optimization studies of ERT monitoring schemes have mainly focused on surface ERT, whereas cross-hole ERT (CHERT) has received far less attention.
Methods Due to the advantages of CHERT in high-precision characterization, this study proposes using Bayesian experimental design to optimize CHERT monitoring scheme. Through laboratory static and dynamic tests and a field application, data acquisition time and imaging accuracy between the optimized and traditional electrode configurations to evaluate the effectiveness of the Bayesian-based optimization.
Results Laboratory tests demonstrate that the optimized monitoring scheme can reduce acquisition time by approximately 75%, and the inversion results more accurately delineate the evolving resistivity anomaly zones, thereby mitigating the lag effect observed in traditional schemes. The field application shows that the optimized scheme can reduce monitoring time by approximately 95%.
Conclusion The optimization of CHERT electrode configurations based on Bayesian experimental design provides a technical basis for efficient monitoring of 4D hydrogeological processes.
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图 2 研究场地跨孔ERT数据概化模型
Figure 2. Generalized model with cross-hole ERT data in the study site
图 3 静态实验电阻异常体反演结果标准化图
Figure 3. Normalized inversion results for the resistivity anomaly in the static test
图 4 动态实验电阻异常体反演结果标准化图
a~e.
1249 组Bipole-Bipole电极排列；f~j. 250组优化电极排列Figure 4. Normalized inversion results for the resistivity anomaly in the dynamic test
图 5 不同电极排列测得异常体与实际异常体的质心坐标 (a) 及其之间的质心距 (b)
Figure 5. Centroid coordinates of the anomaly measured by different electrode configurations and the actual anomaly(a) and centroid distances between the anomaly measured by different electrode configurations and the actual anomaly (b)
图 6 不同电极排列测得异常体质心坐标 (a) 及其与实际异常体质心距 (b) 的均方根误差（RMSE）
Figure 6. Root-mean-square errors of centroid coordinates of the anomaly measured by different electrode configurations (a) and root-mean-square errors of centroid distances between the anomaly measured by different electrode configurations and the actual anomaly (b)
图 7 Bipole-Bipole电极排列的2种不同排列方式
A，B. 电流电极；M，N. 电位电极；下同
Figure 7. Two arrangements for Bipole-Bipole electrode configurations
图 8 Bipole-Bipole电极排列的2种不同排列方式的灵敏度分布图
Figure 8. Sensitivity distributions of two arrangements for Bipole-Bipole electrode configurations
图 9 不同电极排列的总灵敏度分布图
Figure 9. Total sensitivity distributions for different electrode configurations
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