Identifying the source settings of deep brine leakage from CO2 geological repositories using observations from shallow overlying formations
Identifying the source settings of deep brine leakage from CO2 geological repositories using observations from shallow overlying formations
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DOI：
10.1016/j.advwatres.2023.104505
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发表时间：
2023-07-21
影响因子：
4.7
通讯作者：
Illangasekare，Tissa H.
中科院分区：
文献类型：
--
作者：
Askar，Ahmad H.;White，Jeremy T.;Illangasekare，Tissa H.
浅层地下水资源覆盖在碳储存应用中使用的深层盐岩层上，受到CO2/盐水泄漏的潜在污染威胁，这些泄漏是通过封闭盖层中的自然或人为诱导的传导路径进行的。确定泄漏源的位置和速率对于制定补救计划和设计纠正措施至关重要。由于有关深层区域流动和输运特征的信息有限，以及获得其对CO2注入操作的响应数据的成本高，因此估计准确的源设置（即，位置和速率）可能极具挑战性。在这种情况下，贝叶斯逆框架成为有用的工具，以帮助确定潜在的泄漏模式。本研究测试和验证了一个集成为基础的数据同化方法，减少了不确定性的先验知识的源设置通过调节前向传输模型使用相对便宜的易于获取的浅区数据。该方法结合了新开发的合奏平滑工具的反演代码“PEST++”与运输代码“FEFLOW”进行历史匹配和不确定性分析。在标定过程中，采用了一种新的参数化方法，允许潜在源的配置，以搜索泄漏的位置。在现场数据的情况下，该方法进行了验证，使用的实验数据产生的1.88米长的土槽模拟渗漏从存储区迁移到浅层含水层。结果表明，源位置的不确定性可以合理地减少使用浅区数据收集的近地表含水层。然而，关于系统的更多先验信息和更深层次的数据对于估计泄漏率的实际概率范围是必不可少的。
Shallow groundwater resources overlaying deep saline formations used in carbon storage applications are subjected to a potential contamination threat by CO2/brine leakage via natural or anthropogenically-induced conductive pathways in the confining caprock. Identifying the leakage source location and rate is critical for developing remediation plans and designing corrective actions. Owing to limited information about the flow and transport characteristics of deep regimes and high cost of obtaining data on their response to CO2injection operation, estimating accurate source settings (i.e., location and rate) can be extremely challenging. Under such conditions, Bayesian inverse frameworks become useful tools to help identify potential leakage patterns. This study tests and validates an ensemble-based data-assimilation approach that reduces the uncertainty in the prior knowledge about source settings through conditioning forward transport models using relatively inexpensive easy-to-acquire shallow zone data. The approach incorporates the newly developed ensemble smoother tool in the inversion code “PEST++” with the transport code “FEFLOW” to perform history matching and uncertainty analysis. A novel parameterization method that allows the disposition of potential source was used to search the leakage location during calibration process. In the absence of field data, the approach was validated using experimental data generated in ∼8 m long soil tank simulating leakage from storage zone migrating to the shallow aquifer. The results show that source location uncertainty can be reasonably reduced using shallow zone data collected from near-surface aquifers. However, more prior information about the system and deeper data are essential to estimate a practical probability range for the leakage rate.