Monitoring Brine Leakage From Deep Geologic Formations Storing Carbon Dioxide: Design Framework Validation Using Intermediate‐Scale Experiment
Monitoring Brine Leakage From Deep Geologic Formations Storing Carbon Dioxide: Design Framework Validation Using Intermediate‐Scale Experiment
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DOI：
10.1029/2021wr031005
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发表时间：
2021-12
影响因子：
5.4
通讯作者：
A. H. Askar;T. Illangasekare;Ana Maria Carmen Ilie
中科院分区：
文献类型：
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作者：
A. H. Askar;T. Illangasekare;Ana Maria Carmen Ilie
监测二氧化碳地质储存库（CGS）的盐水泄漏对于保护浅层含水层免受污染是必要的。开发并验证了设计CGS监测系统的框架，该系统可以最佳地使用易于获得的浅层数据和难以获得的深区观测数据。该框架基于使用监测数据校准输送模型，以确定泄漏源条件，然后预测随后可能污染浅层含水层的盐水羽流。由于成本方面的考虑将限制对深层地层的监测，因此开发了该框架，以尽量减少深层观测点（例如深层传感器）的数量。在此框架下，将线性不确定性分析与遗传算法相结合，选择出最有价值的监测位置，以降低预测不确定性。由于实际的挑战，在现场测试这样一个框架是不可行的。因此，该框架在一个中等规模的土壤槽中进行了测试，在那里收集了从储存区到浅层含水层的盐水泄漏羽流发展的监测数据。然后，将根据这些数据校准的传输模型做出的预测与实验测量结果进行比较，以评估数据的信息性，从而验证框架的适用性。结果表明，该框架能够为泄漏检测和模型校准选择最佳监测位置。我们还发现，不仅是深层观测资料，而且浅层资料也有确定源条件的价值。此外，研究结果表明，利用早期监测数据识别浅层含水层中可能受到影响的区域是可能的。
Monitoring brine leakage from CO2 geological storages (CGS) is necessary to protect shallow aquifers against contamination. A framework for designing CGS monitoring systems that optimally use both easily available shallow zone data and hard‐to‐obtain deep zone observations is developed and validated. This framework is based on calibrating a transport model using monitoring data to determine leakage source conditions and then predict the subsequent brine plume that potentially contaminates shallow aquifers. As cost considerations are expected to limit monitoring deep formations, the framework is developed to minimize the number of deep observation points (e.g., deep sensors). The best monitoring locations that yield the most worthful data for reducing predictive uncertainty is selected by integrating linear uncertainty analysis with Genetic Algorithm under this framework. Due to practical challenges, testing such a framework in the field is not feasible. Thus, the framework was tested in an intermediate‐scale soil tank, where monitoring data on brine leakage plume development from the storage zone to the shallow aquifer were collected. Predictions made by a transport model calibrated on these data were then compared with experimental measurements to evaluate data informativity and thus validate the framework's applicability. The results demonstrate the framework ability to select the optimum monitoring locations for leakage detection and model calibration. It was also found that not only deep observations, but also shallow zone data are worthful to determine source conditions. Moreover, the results showed the possibility of identifying the likely areas to be impacted in the shallow aquifer using early stage monitoring data.