As the global deployment of carbon capture and sequestration (CCS) technology intensifies in the fight against climate change, it becomes increasingly imperative to establish robust monitoring and detection mechanisms for potential underground CO2 leakage, particularly through pre-existing or induced faults in the storage reservoir's seals. While techniques such as history matching and time-lapse seismic monitoring of CO2 storage have been used successfully in tracking the evolution of CO2 plumes in the subsurface, these methods lack principled approaches to characterize uncertainties related to the CO2 plumes' behavior. Inclusion of systematic assessment of uncertainties is essential for risk mitigation for the following reasons: (i) CO2 plume-induced changes are small and seismic data is noisy; (ii) changes between regular and irregular (e.g., caused by leakage) flow patterns are small; and (iii) the reservoir properties that control the flow are strongly heterogeneous and typically only available as distributions. To arrive at a formulation capable of inferring flow patterns for regular and irregular flow from well and seismic data, the performance of conditional normalizing flow will be analyzed on a series of carefully designed numerical experiments. While the inferences presented are preliminary in the context of an early CO2 leakage detection system, the results do indicate that inferences with conditional normalizing flows can produce high-fidelity estimates for CO2 plumes with or without leakage. We are also confident that the inferred uncertainty is reasonable because it correlates well with the observed errors. This uncertainty stems from noise in the seismic data and from the lack of precise knowledge of the reservoir's fluid flow properties.

翻译：随着全球为应对气候变化而加速部署碳捕集与封存（CCS）技术，建立稳健的监测与检测机制以应对地下CO2潜在泄漏（尤其是通过储层盖层中既有或诱发断层发生的泄漏）变得愈发迫切。尽管历史拟合、时移地震监测等技术已成功用于追踪地下CO2羽流的演化，但这些方法缺乏表征CO2羽流行为相关不确定性的原则性方法。将系统性的不确定性评估纳入风险缓释至关重要，原因在于：（i）CO2羽流引起的变化微小，且地震数据存在噪声；（ii）规则流与不规则流（例如由泄漏引起）之间的差异微小；（iii）控制流动的储层性质具有强非均质性，通常仅能以分布形式获取。为构建能够从井数据和地震数据推断规则与不规则流动模式的公式体系，本研究将通过一系列精心设计的数值实验分析条件归一化流的性能。尽管所呈现的推断结论在早期CO2泄漏检测系统的背景下尚属初步，但结果表明，条件归一化流能够对有无泄漏的CO2羽流产生高保真估计。此外，我们确信推断的不确定性是合理的，因其与观测误差具有良好相关性。这种不确定性源于地震数据中的噪声以及储层流体流动特性的精确知识缺失。