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A New Randomized Binary Prior Model for Hydraulic Tomography in Fractured Aquifers
Ground Water ( IF 2.6 ) Pub Date : 2021-01-18 , DOI: 10.1111/gwat.13074
Sarada Poduri 1 , Bvnp Kambhammettu 1 , Saisrinivas Gorugantula 1
Affiliation  

We present a novel pilot-point-based hydraulic tomography (HT) inversion procedure to delineate preferential flow paths and estimate hydraulic properties in a fractured aquifer. Our procedure considers a binary prior model developed using a randomized algorithm. The randomized algorithm involves discretizing the domain into grid cells, assigning a binary label to each cell, traversing the grid randomly, and choosing the optimal grid configuration cell-by-cell. This binary prior model is used to guide the placement of pilot points and to constrain aquifer parameters during pilot-point-based HT inversion. A two-dimensional fractured granite rock block was considered to test our methodology under controlled laboratory conditions. Multiple pumping tests were conducted at selected ports and the pressure responses were monitored. The pumping datasets thus obtained were preprocessed using median filters to remove random noise, and then analyzed using the proposed procedure. The proposed binary prior algorithm was implemented in C++ by supplying the forward groundwater model, HydroGeoSphere (HGS). Pilot-point-assisted HT inversion was performed using the parameter-estimation tool, coupled to HGS. The resulting parameter distributions were assessed by: (1) a visual comparison of the K- and Ss-tomograms with the known topology of the fractures and (2) comparing model predictions with measurements made at two validation ports that were not used in calibration. The performance assessment revealed that HT with the proposed randomized binary prior could be used to recover fracture-connectivity and to predict drawdowns in fractured aquifers with reasonable accuracy, when compared to a conventional pilot-point inversion scheme.

中文翻译:

裂隙含水层水力层析成像的一种新的随机二元先验模型

我们提出了一种新的基于先导点的水力层析成像 (HT) 反演程序,以描绘优先流动路径并估计裂缝含水层中的水力特性。我们的程序考虑了使用随机算法开发的二元先验模型。随机算法涉及将域离散为网格单元,为每个单元分配一个二进制标签,随机遍历网格,并逐个单元选择最佳网格配置。这种二元先验模型用于在基于先导点的 HT 反演过程中指导先导点的放置和约束含水层参数。考虑在受控实验室条件下使用二维断裂花岗岩块来测试我们的方法。在选定的端口进行了多次泵送测试,并监测了压力响应。使用中值滤波器对由此获得的抽水数据集进行预处理以去除随机噪声,然后使用所提出的程序进行分析。通过提供前向地下水模型 HydroGeoSphere (HGS),在 C++ 中实现了所提出的二元先验算法。先导点辅助 HT 反演是使用参数估计工具执行的,与 HGS 耦合。通过以下方式评估所得参数分布:(1)视觉比较具有已知裂缝拓扑结构的KS s断层图,以及 (2) 将模型预测与在校准中未使用的两个验证端口进行的测量进行比较。性能评估表明,与传统的先导点反演方案相比,具有建议的随机二元先验的 HT 可用于恢复裂缝连通性并以合理的精度预测裂缝含水层的水位下降。
更新日期:2021-01-18
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