CESEP Brine Leakage Control Experiment

The Center for Experimental Study of Subsurface Environmental Processes (CESEP) conducted an intermediate-scale laboratory experiment to validate a developed approach for designing control systems for the potential brine leakage from CO2 storage zones. The developed approach applies the technique of deep brine extraction to control the leakage, thus it incorporates the global optimizer of Genetic Algorithm (GA) and a FEFLOW-based transport model to find the best extraction locations in the storage zone that minimizes the needed amount of extracted brine. In an ~8m long soil tank, a brine leakage plume was controlled using the extraction system designed based on the GA results. Collected data was then used to first make sure that the GA results and boundary conditions were accurately applied in the experiment and second to evaluate whether the observed plume concentrations in the shallow aquifer met the predefined constraining limits in the optimization problem. Acquired data during the experiment included transient measurements of the injection and extraction flow rates as well as plume concentrations. The conducted experiment and the testing system are described in detail in a research article developed by the dataset authors and entitled \"Monitoring Brine Leakage from Deep Geologic Formations Storing Carbon Dioxide: Design Framework Validation Using Intermediate-Scale Experiment\". For any questions, users are referred to the data owners.

地下环境过程实验研究中心（Center for Experimental Study of Subsurface Environmental Processes，CESEP）开展了一项中等规模室内实验，旨在验证一种用于设计二氧化碳封存带潜在盐水泄漏控制系统的研发方法。该方法采用深部盐水抽取技术管控泄漏风险，整合了遗传算法（Genetic Algorithm，GA）全局优化器与基于FEFLOW的运移模型，用于确定封存带内最优抽取位置，以最小化所需抽取的盐水总量。在一个长约8米的土槽中，研究人员采用基于GA结果设计的抽取系统对盐水泄漏羽流进行了管控。所收集的数据首先用于验证实验中GA结果与边界条件的应用准确性，其次用于评估浅层含水层中观测到的羽流浓度是否满足优化问题中预设的约束限值。实验期间采集的数据包括注入与抽取流量的瞬态测量值以及羽流浓度数据。本实验与测试系统的详细描述已发表于数据集作者撰写的题为《封存二氧化碳的深部地质构造盐水泄漏监测：基于中等规模实验的设计框架验证》的研究论文中。如有任何疑问，请联系数据所有者。